Publications

JOURNAL PAPERS (SUBMITTED)

[1]   M. Korbit, A.D. Adeoye, A. Bemporad, and M. Zanon, “Exact Gauss-Newton optimization for training deep neural networks,” 2024, submitted for publication. Available on arXiv at http://arxiv.org/abs/2405.14402.

[2]   S.K. Mulagaleti and A. Bemporad, “Combined learning of linear parameter-varying models and robust control invariant sets,” 2024, submitted for publication. Available on arXiv at https://arxiv.org/abs/2411.18166.

[3]   A. Bemporad, “An L-BFGS-B approach for linear and nonlinear system identification under ℓ₁- and group-lasso regularization,” 2024, submitted for publication. Available on arXiv at http://arxiv.org/abs/2403.03827.

[4]   G. Cimini, M. Gatti, D. Bernardini, A. Bemporad, C. Audas, and C.-G. Dussap, “Towards supervisory model predictive control for circular life support systems in long-term space missions,” 2024, submitted for publication.

[5]   S. Ruiz-Moreno, A. Bemporad, A.J. Gallego, and E.F. Camacho, “System identification and fault reconstruction in solar plants via extended Kalman filter-based training of recurrent neural networks,” 2024.

[6]   M. Zhu and A. Bemporad, “Global and preference-based optimization with mixed variables using piecewise affine surrogates,” 2024, Submitted for publication. Paper: https://arxiv.org/abs/2302.04686, code: https://github.com/mjzhu-p/PWAS.

[7]   R. Reiter, A. Nurkanovic, D. Bernardini, M. Diehl, and A. Bemporad, “A long-short-term mixed-integer formulation for highway motion planning,” IEEE Transactions on Intelligent Vehicles, 2024, accepted for publication.

[8]   M. Zhu, A. Mroz, L. Gui, K.E. Jelfs, A. Bemporad, E.A. del Río Chanona, and Y.S. Lee, “Discrete and mixed-variable experimental design with surrogate-based approach,” Digital Discovery, 2024.

[9]   P. Krupa, M. Zanon, and A. Bemporad, “Learning disturbance models for offset-free reference tracking,” 2023, Submitted for publication. https://arxiv.org/abs/2312.11409.

[10]   P. Krupa, D. Limon, A. Bemporad, and T. Alamo, “Harmonic model predictive control for tracking periodic references,” 2023, Submitted for publication. Available on http://arxiv.org/abs/2310.16723.

[11]   A.D. Adeoye and A. Bemporad, “Self-concordant smoothing for large-scale convex composite optimization,” 2023, Submitted for publication. https://arxiv.org/abs/2309.01781.

[12]   S. Soman, M. Zanon, and A. Bemporad, “Learning-based stochastic model predictive control for autonomous driving at uncontrolled intersections,” 2023, submitted for publication.

JOURNAL PAPERS (IN PRESS)

[13]   F. Fabiani and A. Bemporad, “An active learning method for solving competitive multi-agent decision-making and control problems,” IEEE Transactions on Automatic Control, 2025, in press. Also available on http://arxiv.org/abs/2212.12561.

[14]   S.K. Mulagaleti, M. Mejari, and A. Bemporad, “Parameter dependent robust control invariant sets for LPV systems with bounded parameter variation rate,” IEEE Transactions on Automatic Control, 2023, in press.

[15]   A.D. Adeoye and A. Bemporad, “An inexact sequential quadratic programming method for learning and control of recurrent neural networks,” IEEE Transactions on Neural Networks and Learning Systems, 2024, in press.

[16]   F. Badalamenti, S.K. Mulagaleti, A. Bemporad, B. Houska, and M.E. Villanueva, “Configuration-constrained tube MPC for tracking,” IEEE Control Systems Letters, 2024, accepted for publication. Also available on arXiv at https://arxiv.org/abs/2405.03629.

BOOKS

[17]   A. Bemporad, W.P.M.H. Heemels, and M. Johansson (Eds.), Networked Control Systems, vol. 406 of Lecture Notes in Control and Information Sciences, Springer-Verlag, Berlin Heidelberg, 2010, http://cse.lab.imtlucca.it/hybrid/wide/school09/.

[18]   A. Bemporad, A. Bicchi, and G. Buttazzo (Eds.), Hybrid Systems: Computation and Control, Proceedings of the 10th International Conference, vol. 4416 of Lecture Notes in Computer Science, Springer-Verlag, Berlin Heidelberg, Apr. 2007, 797 p., ISBN: 978-3-540-71492-7, http://cse.lab.imtlucca.it/~bemporad/hybrid/hscc07.

[19]   F. Borrelli, A. Bemporad, and M. Morari, Predictive control for linear and hybrid systems, Cambridge University Press, 2017.

JOURNAL PAPERS

[20]   S. Abdufattokhov, M. Zanon, and A. Bemporad, “Learning Lyapunov terminal costs from data for complexity reduction in nonlinear model predictive control,” Int. J. Robust Nonlinear Control, vol. 34, no. 13, pp. 8676–8691, 2024.

[21]   S.K. Mulagaleti, A. Bemporad, and M. Zanon, “Computation of safe disturbance sets using implicit RPI sets,” IEEE Transactions on Automatic Control, vol. 69, no. 7, pp. 4443–4458, 2024.

[22]   A.K. Sampathirao, P. Patrinos, A. Bemporad, and P. Sopasakis, “Massively parallelizable proximal algorithms for large-scale stochastic optimal control problems,” Optimal Control, Applications and Methods, vol. 45, no. 1, pp. 45–63, 2024.

[23]    A. Oleinikov, S. Soltan, Z. Balgabekova, A. Bemporad, and M. Rubagotti, “Scenario-based model predictive control with probabilistic human predictions for human-robot coexistence,” Control Engineering Practice, vol. 142, pp. 105769, 2024.

[24]   P. Krupa, O. Inverso, M. Tribastone, and A. Bemporad, “Certification of the proximal gradient method under fixed-point arithmetic for box-constrained QP problems,” Automatica, vol. 159, pp. 111411, 2024.

[25]   A.D. Adeoye and A. Bemporad, “SCORE: Approximating curvature information under self-concordant regularization,” Computational Optimization and Applications, vol. 86, no. 2, pp. 599–626, 2023.

[26]   M. Mejari, S.K. Mulagaleti, and A. Bemporad, “Data-driven synthesis of configuration-constrained robust invariant sets for linear parameter-varying systems,” IEEE Control Systems Letters, vol. 7, pp. 3818–3823, 2023, also in Proc. American Contr. Conf., Toronto, Canada, July 8-12, 2024.

[27]   A. Bemporad, “Recurrent neural network training with convex loss and regularization functions by extended Kalman filtering,” IEEE Transactions on Automatic Control, vol. 68, no. 9, pp. 5661–5668, 2023.

[28]   A. Bemporad, “A piecewise linear regression and classification algorithm with application to learning and model predictive control of hybrid systems,” IEEE Transactions on Automatic Control, vol. 68, no. 6, pp. 3194–3209, June 2023, code available at http://cse.lab.imtlucca.it/~bemporad/parc.

[29]   A. Bemporad, “Training recurrent neural networks by sequential least squares and the alternating direction method of multipliers,” Automatica, vol. 156, pp. 111183, October 2023.

[30]   A. Bemporad, “Active learning for regression by inverse distance weighting,” Information Sciences, vol. 626, pp. 275–292, May 2023, also available on http://arxiv.org/abs/2204.07177. Code availble at http://cse.lab.imtlucca.it/~bemporad/ideal.

[31]   K.F. Løwenstein, L. Fagiano, D. Bernardini, and A. Bemporad, “Physics-informed online learning of gray-box models by moving horizon estimation,” European Journal of Control, vol. 74, pp. 100861, Nov. 2023, in press. Also in Proc. European Control Conference, Bucharest, Romania, 2023.

[32]   D. Masti, V. Breschi, S. Formentin, and A. Bemporad, “Auto-tuning of reference models in direct data-driven control,” Automatica, vol. 155, pp. 111110, 2023.

[33]   A. Bemporad and G. Cimini, “Variable elimination in model predictive control based on K-SVD and QR factorization,” IEEE Transactions on Automatic Control, vol. 68, no. 2, pp. 782–797, 2023.

[34]   L. Wu and A. Bemporad, “A simple and fast coordinate-descent augmented-Lagrangian solver for model predictive control,” IEEE Transactions on Automatic Control, vol. 68, no. 11, pp. 6860–6866, 2023.

[35]   M. Facchino, M. Zanon, and A. Bemporad, “Continuous-time formulation of a first-order equivalence between a tracking and an economic MPC,” IEEE Control Systems Letters, vol. 7, pp. 2197–2202, 2023, in press. Also in Proc. IEEE Conf. on Decision and Control, 2023.

[36]   D. Masti, F. Fabiani, G. Gnecco, and A. Bemporad, “Counter-example guided inductive synthesis of control Lyapunov functions for uncertain systems,” IEEE Control Systems Letters, vol. 7, pp. 2047–2052, 2023, also in Proc. IEEE Conf. on Decision and Control, 2023, and available at https://arxiv.org/abs/2303.10024.

[37]   K. Seel, A. Bemporad, S. Gros, and J.T. Gravdahl, “Variance-based exploration for learning model predictive control,” IEEE Access, vol. 11, pp. 60724–60736, 2023.

[38]   S.K. Mulagaleti, A. Bemporad, and M. Zanon, “Computation of input disturbance sets for constrained output reachability,” IEEE Transactions on Automatic Control, vol. 68, no. 6, pp. 3573–3580, June 2023.

[39]   L. Cannelli, M. Zhu, F. Farina, A. Bemporad, and D. Piga, “Multi-agent active learning for distributed black-box optimization,” IEEE Control Systems Letters, vol. 7, pp. 1488–1493, 2023.

[40]   A. Ravera, A. Oliveri, M. Lodi, A. Bemporad, W.P.M.H. Heemels, E.C. Kerrigan, and M. Storace, “Co-design of a controller and its digital implementation: the MOBY-DIC2 toolbox for embedded model predictive control,” IEEE Transactions on Control Systems Technology, vol. 31, no. 6, pp. 2871–2878, 2023.

[41]   S.K. Mulagaleti, A. Bemporad, and M. Zanon, “Data-driven synthesis of robust invariant sets and controllers,” IEEE Control Systems Letters, vol. 6, pp. 1676–1681, 2022.

[42]   F. Bianchi, L. Piroddi, A. Bemporad, G. Halasz, M. Villani, and D. Piga, “Active preference-based optimization for human-in-the-loop feature selection,” European Journal of Control, vol. 66, pp. 100647, 2022.

[43]   M. Zanon and A. Bemporad, “Constrained control and observer design by inverse optimality,” IEEE Transactions on Automatic Control, vol. 67, no. 10, pp. 5432–5439, Oct. 2022.

[44]   S.K. Mulagaleti, A. Bemporad, and M. Zanon, “Input constraint sets for robust regulation of linear systems,” IEEE Transactions on Automatic Control, vol. 67, no. 10, pp. 5533–5540, Oct. 2022.

[45]   M. Zhu, D. Piga, and A. Bemporad, “C-GLISp: Preference-based global optimization under unknown constraints with applications to controller calibration,” IEEE Transactions on Control Systems Technology, vol. 30, no. 3, pp. 2176–2187, Sept. 2022, also available on arXiv at https://arxiv.org/pdf/2106.05639.

[46]   D. Arnström, A. Bemporad, and D. Axehill, “A dual active-set solver for embedded quadratic programming using recursive LDL^T updates,” IEEE Transactions on Automatic Control, vol. 67, no. 8, pp. 4362–4369, 2022.

[47]   N. Saraf and A. Bemporad, “An efficient bounded-variable nonlinear least-squares algorithm for embedded MPC,” Automatica, vol. 141, pp. 110293, 2022.

[48]   D. Arnström, A. Bemporad, and D. Axehill, “A linear programming method based on proximal-point iterations with applications to multi-parametric programming,” IEEE Control Systems Letters, vol. 6, pp. 2066–2071, 2022.

[49]   S. Simić, A. Bemporad, O. Inverso, and M. Tribastone, “Tight error analysis in fixed-point arithmetic,” Formal Aspects of Computing, vol. 34, no. 1, pp. 1–32, 2022.

[50]   L. Roveda, B. Maggioni, E. Marescotti, A.A. Shahid, A.M. Zanchettin, A. Bemporad, and D. Piga, “Pairwise preferences-based optimization for velocity planning in robotic sealing tasks,” IEEE Robotics and Automation Letters, vol. 6, no. 2, pp. 6632–6639, 2021, also presented at the 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[51]   N. Rathod, A. Bratta, M. Focchi, M. Zanon, O.A. Villarreal Magaña, C. Semini, and A. Bemporad, “Model predictive control with environment adaptation for legged locomotion,” IEEE Access, vol. 9, pp. 145710–145727, 2021.

[52]   D. Masti, M. Zanon, and A. Bemporad, “Tuning LQR controllers: a sensitivity-based approach,” IEEE Control Systems Letters, vol. 6, pp. 932–937, 2022, also in Proc. 60th IEEE Conf. on Decision and Control, Austin, TX, December 13-15, 2021.

[53]   R.A.E. Zidek, I.V. Kolmanovsky, and A. Bemporad, “Model predictive control for drift counteraction of stochastic constrained linear systems,” Automatica, vol. 123, pp. 109304, 2021.

[54]   D. Arnström, A. Bemporad, and D. Axehill, “Complexity certification of proximal-point methods for numerically stable quadratic programming,” IEEE Control Systems Letters, vol. 5, no. 4, pp. 1381–1386, 2021, also in Proc. American Control Conference, New Orleans, LA, USA, 2021.

[55]   D. Masti, D. Bernardini, and A. Bemporad, “A machine-learning approach to synthesize virtual sensors for estimating the scheduling signal of parameter-varying systems,” European Journal of Control, vol. 61, pp. 40–49, 2021.

[56]   D. Masti and A. Bemporad, “Learning nonlinear state-space models using autoencoders,” Automatica, vol. 129, pp. 109666, 2021.

[57]   A. Bemporad and D. Piga, “Active preference learning based on radial basis functions,” Machine Learning, vol. 110, no. 2, pp. 417–448, 2021, Available on arXiv at http://arxiv.org/abs/1909.13049. Code available at http://cse.lab.imtlucca.it/~bemporad/glis.

[58]   G. Cimini, D. Bernardini, S. Levijoki, and A. Bemporad, “Embedded model predictive control with certified real-time optimization for synchronous motors,” IEEE Transactions on Control Systems Technology, vol. 29, no. 2, pp. 893–900, Mar. 2021.

[59]   D. Selvi, D. Piga, G. Battistelli, and A. Bemporad, “Optimal direct data-driven control with stability guarantees,” European Journal of Control, vol. 59, pp. 175–187, 2021.

[60]   A. Bemporad, “Global optimization via inverse distance weighting and radial basis functions,” Computational Optimization and Applications, vol. 77, pp. 571–595, 2020, code available at http://cse.lab.imtlucca.it/~bemporad/glis.

[61]   D. Piga, V. Breschi, and A. Bemporad, “Estimation of jump Box-Jenkins models,” Automatica, vol. 120, pp. 109126, 2020.

[62]   V. Breschi, A. Bemporad, and I.V. Kolmanovsky, “Cooperative constrained parameter estimation by ADMM-RLS,” Automatica, vol. 121, pp. 109175, 2020.

[63]   D. Rubin, P. Mercader, P.-O. Gutman, H.-N. Nguyen, and A. Bemporad, “Interpolation based predictive control by ellipsoidal invariant sets,” IFAC Journal of Systems and Control, vol. 12, pp. 100084, 2020.

[64]   D. Piga, A. Bemporad, and A. Benavoli, “Rao-Blackwellized sampling for batch and recursive Bayesian inference of piecewise affine models,” Automatica, vol. 117, pp. 109002, 2020.

[65]   N. Saraf and A. Bemporad, “A bounded-variable least-squares solver based on stable QR updates,” IEEE Transactions on Automatic Control, vol. 65, no. 3, pp. 1242–1247, 2020.

[66]   D. Arnström, A. Bemporad, and D. Axehill, “Exact complexity certification of a nonnegative least-squares method for quadratic programming,” IEEE Control Systems Letters, vol. 4, no. 4, pp. 1036–1041, 2020, also in Proc. 59th IEEE Conf. Decision and Control, Jeju Island (South Korea), 2020.

[67]   D. Arnström, A. Bemporad, and D. Axehill, “Complexity certification of proximal-point methods for numerically stable quadratic programming,” IEEE Control Systems Letters, vol. 5, no. 4, pp. 1381–1386, 2020, also in Proc. American Control Conference, New Orleans, LA, 2021.

[68]   B. Stellato, G. Banjac, P. Goulart, A. Bemporad, and S. Boyd, “OSQP: An operator splitting solver for quadratic programs,” Mathematical Programming Computation, vol. 12, pp. 637–672, 2020, http://arxiv.org/abs/1711.08013, Code avaliable at https://github.com/oxfordcontrol/osqp. Awarded best paper of the journal for year 2020.

[69]   S.K. Mulagaleti, A. Bemporad, and M. Zanon, “Computation of least-conservative state-constraint sets for decentralized MPC with dynamic and constraint coupling,” IEEE Control Systems Letters, vol. 5, no. 1, pp. 235–240, 2020, also in Proc. 59th IEEE Conf. Decision and Control, Jeju Island (Korea), 2020.

[70]   M.D. Mejari, V.V. Naik, D. Piga, and A. Bemporad, “Identification of hybrid and linear parameter-varying models via piecewise affine regression using mixed integer programming,” Int. J. Robust Nonlinear Control, vol. 30, pp. 5802–5819, 2020.

[71]   R. Takapoui, N. Moehle, S. Boyd, and A. Bemporad, “A simple effective heuristic for embedded mixed-integer quadratic programming,” Int. J. Control, vol. 93, no. 1, pp. 2–12, 2020.

[72]   S. Gros, M. Zanon, R. Quirynen, A. Bemporad, and M. Diehl, “From linear to nonlinear MPC: bridging the gap via the real-time iteration,” Int. J. Control, vol. 93, no. 1, pp. 62–80, 2020.

[73]   G. Cimini and A. Bemporad, “Complexity and convergence certification of a block principal pivoting method for box-constrained quadratic programs,” Automatica, vol. 100, pp. 29–37, 2019.

[74]   M. Graf Plessen, L. Puglia, T. Gabbriellini, and A. Bemporad, “Dynamic option hedging with transaction costs: A stochastic model predictive control approach,” Int. J. Robust Nonlinear Control, vol. 29, pp. 5058–5077, 2019.

[75]   V. Breschi, D. Piga, and A. Bemporad, “Online end-use energy disaggregation via jump linear models,” Control Engineering Practice, vol. 89, pp. 30–42, 2019.

[76]   P. Sopasakis, D. Herceg, A. Bemporad, and P. Patrinos, “Risk-averse model predictive control,” Automatica, vol. 100, pp. 281–288, 2019.

[77]   D. Piga, M. Forgione, S. Formentin, and A. Bemporad, “Performance-oriented model learning for data-driven MPC design,” IEEE Control Systems Letters, vol. 3, no. 3, pp. 577–582, July 2019, also in Proc. 58th IEEE Conf. Decision and Control, Nice (France), 2019. https://arxiv.org/abs/1904.10839.

[78]   P. Sopasakis, A.K. Sampathirao, A. Bemporad, and P. Patrinos, “Uncertainty-aware demand management of water distribution networks in deregulated energy markets,” Environmental Modelling & Software, vol. 101, pp. 10–22, Mar. 2018, https://github.com/GPUEngineering/RapidNet.

[79]   M. Graf Plessen and A. Bemporad, “A posteriori multistage optimal trading under transaction costs and a diversification constraint,” The Journal of Trading, vol. 13, no. 3, pp. 67–83, 2018.

[80]   A. Bemporad, V. Breschi, D. Piga, and S. Boyd, “Fitting jump models,” Automatica, vol. 96, pp. 11–21, Oct. 2018, also available on arXiv at http://arxiv.org/abs/1711.09220. Code available at http://cse.lab.imtlucca.it/~bemporad/jump_models/.

[81]   A. Bemporad, “A numerically stable solver for positive semi-definite quadratic programs based on nonnegative least squares,” IEEE Transactions on Automatic Control, vol. 63, no. 2, pp. 525–531, 2018.

[82]   D. Piga, S. Formentin, and A. Bemporad, “Direct data-driven control of constrained systems,” IEEE Transactions on Control Systems Technology, vol. 26, no. 4, pp. 1422–1429, July 2018.

[83]   Z. Liu, L. Xie, A. Bemporad, and S. Lu, “Fast linear parameter varying model predictive control of buck DC-DC converters based on FPGA,” IEEE ACCESS, vol. 6, pp. 52434–52446, 2018.

[84]   R.A.E. Zidek, I.V. Kolmanovsky, and A. Bemporad, “Spacecraft drift counteraction optimal control: Computationally efficient open-loop and receding horizon solutions,” AIAA Journal of Guidance, Control, and Dynamics, vol. 41, no. 965, pp. 1859–1872, 2018.

[85]   G. Cimini and A. Bemporad, “Exact complexity certification of active-set methods for quadratic programming,” IEEE Transactions on Automatic Control, vol. 62, no. 12, pp. 6094–6109, 2017.

[86]   A.K. Sampathirao, P. Sopasakis, A. Bemporad, and P. Patrinos, “GPU-accelerated stochastic predictive control of drinking water networks,” IEEE Transactions on Control Systems Technology, vol. 26, no. 2, pp. 551–562, Mar. 2018.

[87]   G. Serale, M. Fiorentini, A. Capozzoli, D. Bernardini, and A. Bemporad, “Model predictive control (MPC) for enhancing buildings and HVAC systems energy efficiency: problem formulation, applications and opportunities,” Energies, vol. 11, no. 3, pp. 1–35, 2018.

[88]   M. Mejari, D. Piga, and A. Bemporad, “A bias-correction method for closed-loop identication of linear parameter-varying systems,” Automatica, vol. 87, pp. 128–141, 2018.

[89]   M. Graf Plessen, D. Bernardini, H. Esen, and A. Bemporad, “Spatial-based predictive control and geometric corridor planning for adaptive cruise control coupled with obstacle avoidance,” IEEE Transactions on Control Systems Technology, vol. 26, no. 1, pp. 38–50, 2018.

[90]   G. Gnecco, A. Bemporad, M. Gori, and M. Sanguineti, “LQG online learning,” Neural Computation, vol. 29, no. 8, pp. 2203–2291, 2017.

[91]   S. Sebastio, G. Gnecco, and A. Bemporad, “Optimal distributed task scheduling in volunteer clouds,” Computers and Operations Research, vol. 81, pp. 231–246, 2017.

[92]   M. Graf Plessen and A. Bemporad, “Reference trajectory planning under constraints and path tracking using linear time-varying model predictive control for agricultural machines,” Biosystems Engineering, vol. 153, pp. 28–41, Jan. 2017.

[93]   L. Cavanini, G. Cimini, G. Ippoliti, and A. Bemporad, “Model predictive control for pre-compensated voltage mode controlled DC-DC converters,” IET Control Theory & Applications, vol. 11, no. 15, pp. 2514–2520, 2017.

[94]   A. Khakimova, A. Kusatayeva, A. Shamshimova, D. Sharipova, A. Bemporad, Y. Familiant, A. Shintemirov, V. Ten, and M. Rubagotti, “Optimal energy management of a small-size building via hybrid model predictive control,” Energy and Buildings, vol. 140, pp. 1–8, 2017.

[95]   A. Bemporad, “A quadratic programming algorithm based on nonnegative least squares with applications to embedded model predictive control,” IEEE Transactions on Automatic Control, vol. 61, no. 4, pp. 1111–1116, 2016.

[96]   V. Breschi, D. Piga, and A. Bemporad, “Piecewise affine regression via recursive multiple least squares and multicategory discrimination,” Automatica, vol. 73, pp. 155–162, Nov. 2016.

[97]   M. Rubagotti, L. Zaccarian, and A. Bemporad, “A Lyapunov method for stability analysis of piecewise-affine systems over non-invariant domains,” Int. J. Control, vol. 89, no. 5, pp. 950–959, 2016.

[98]   M. Rubagotti, P. Patrinos, A. Guiggiani, and A. Bemporad, “Real-time model predictive control based on dual gradient projection: Theory and fixed-point FPGA implementation,” Int. J. Robust Nonlinear Control, vol. 26, pp. 3292–3310, 2016.

[99]   R. Morisi, G. Gnecco, and A. Bemporad, “A hierarchical consensus method for the approximation of the consensus state, based on clustering and spectral graph theory,” Engineering Applications of Artificial Intelligence, vol. 56, pp. 157–174, 2016.

[100]   A. Bemporad, “A multiparametric quadratic programming algorithm with polyhedral computations based on nonnegative least squares,” IEEE Transactions on Automatic Control, vol. 60, no. 11, pp. 2892–2903, 2015.

[101]   P. Sopasakis, P. Patrinos, H. Sarimveis, and A. Bemporad, “Model predictive control for linear impulsive systems,” IEEE Transactions on Automatic Control, vol. 60, no. 8, pp. 2277–2282, 2015.

[102]   A. Bemporad and M. Paggi, “Optimization algorithms for the solution of the frictionless normal contact between rough surfaces,” Int. Journal of Solids and Structures, vol. 69-70, pp. 94–105, Sept. 2015.

[103]   P. Patrinos, A. Guiggiani, and A. Bemporad, “A dual gradient-projection algorithm for model predictive control in fixed-point arithmetic,” Automatica, vol. 55, pp. 226–235, 2015.

[104]   G. Gnecco, R. Morisi, and A. Bemporad, “Sparse solutions to the average consensus problem via various regularizations of the fastest mixing markov-chain problem,” IEEE Trans. Network Science and Engineering, vol. 2, no. 3, pp. 97–111, 2015.

[105]   A. Bemporad, L. Bellucci, and T. Gabbriellini, “Dynamic option hedging via stochastic model predictive control based on scenario simulation,” Quantitative Finance, vol. 14, no. 10, pp. 1739–1751, 2014.

[106]   M. Rubagotti, D. Barcelli, and A. Bemporad, “Robust explicit model predictive control via regular piecewise-affine approximation,” Int. J. Control, vol. 87, no. 12, pp. 2583–2593, 2014.

[107]   S. Di Cairano, W.P.M.H. Heemels, M. Lazar, and A. Bemporad, “Stabilizing dynamic controllers for hybrid systems: A hybrid control Lyapunov function approach,” IEEE Transactions on Automatic Control, vol. 59, no. 10, pp. 2629–2643, 2014.

[108]   S. Di Cairano, D. Bernardini, A. Bemporad, and I.V. Kolmanovsky, “Stochastic MPC with learning for driver-predictive vehicle control and its application to HEV energy management,” IEEE Transactions on Control Systems Technology, vol. 22, pp. 1018–1031, 2014.

[109]   M. Rubagotti, P. Patrinos, and A. Bemporad, “Stabilizing linear model predictive control under inexact numerical optimization,” IEEE Transactions on Automatic Control, vol. 59, no. 6, pp. 1660–1666, 2014.

[110]   P. Patrinos and A. Bemporad, “An accelerated dual gradient-projection algorithm for embedded linear model predictive control,” IEEE Transactions on Automatic Control, vol. 59, no. 1, pp. 18–33, 2014.

[111]   P. Patrinos, P. Sopasakis, H. Sarimveis, and A. Bemporad, “Stochastic model predictive control for constrained discrete-time Markovian switching systems,” Automatica, vol. 50, no. 10, pp. 2504–2514, 2014.

[112]   J. Júlvez, S. Di Cairano, A. Bemporad, and C. Mahulea, “Event-driven model predictive control of timed hybrid Petri nets,” Int. J. Robust Nonlinear Control, pp. 1099–1239, 2013.

[113]   M. Rubagotti, T. Poggi, A. Oliveri, C.A. Pascucci, A. Bemporad, and M. Storace, “Low-complexity piecewise-affine virtual sensors: Theory and design,” Int. J. Control, vol. 87, no. 3, pp. 622–632, 2013.

[114]   M. Rubagotti, S. Trimboli, and A. Bemporad, “Stability and invariance analysis of uncertain discrete-time piecewise affine systems,” IEEE Transactions on Automatic Control, vol. 58, no. 9, pp. 2359–2365, 2013.

[115]   S. Di Cairano, H.E. Tseng, D. Bernardini, and A. Bemporad, “Vehicle yaw stability control by coordinating active front steering and differential braking in the tire sideslip angles domain,” IEEE Transactions on Control Systems Technology, vol. 21, no. 4, pp. 1236–1248, July 2013.

[116]   D. Bernardini and A. Bemporad, “Stabilizing model predictive control of stochastic constrained linear systems,” IEEE Transactions on Automatic Control, vol. 57, no. 6, pp. 1468–1480, 2012.

[117]   D. Bernardini and A. Bemporad, “Energy-aware robust model predictive control based on noisy wireless sensors,” Automatica, vol. 48, pp. 36–44, 2012.

[118]   A. Jokic, R.M. Hermans, M. Lazar, A. Alessio, P.P.J. van den Bosch, I.A. Hiskens, and A. Bemporad, “Assessment of non-centralized model predictive control techniques for electrical power networks,” Int. J. Control, vol. 85, no. 8, pp. 1162–1177, 2012.

[119]   T. Poggi, M. Rubagotti, A. Bemporad, and M. Storace, “High-speed piecewise affine virtual sensors,” IEEE Transactions on Industrial Electronics, vol. 59, no. 2, pp. 1228–1237, 2012.

[120]   M.C.F. Donkers, W.P.M.H. Heemels, D. Bernadini, A. Bemporad, and V. Shneer, “Stability analysis of stochastic networked control systems,” Automatica, vol. 48, pp. 917–925, 2012.

[121]   S. Di Cairano, D. Yanakiev, A. Bemporad, I.V. Kolmanovsky, and D. Hrovat, “Model predictive idle speed control: Design, analysis, and experimental evaluation,” IEEE Transactions on Control Systems Technology, vol. 20, no. 1, pp. 84–97, 2012.

[122]   C. Ocampo-Martinez, D. Barcelli, V. Puig, and A. Bemporad, “Hierarchical and decentralised model predictive control of drinking water networks: Application to the Barcelona case study,” IET Control Theory and Applications, vol. 6, no. 1, pp. 62–71, 2012.

[123]   A. Bemporad, A. Oliveri, T. Poggi, and M. Storace, “Ultra-fast stabilizing model predictive control via canonical piecewise affine approximations,” IEEE Transactions on Automatic Control, vol. 56, no. 12, pp. 2883–2897, 2011.

[124]   A. Bemporad and S. Di Cairano, “Model-predictive control of discrete hybrid stochastic automata,” IEEE Transactions on Automatic Control, vol. 56, no. 6, pp. 1307–1321, 2011.

[125]   A. Alessio, D. Barcelli, and A. Bemporad, “Decentralized model predictive control of dynamically-coupled linear systems,” J. Process Control, vol. 21, no. 5, pp. 705–714, June 2011.

[126]   S. Di Cairano and A. Bemporad, “An equivalence result between linear hybrid automata and piecewise affine systems,” IEEE Transactions on Automatic Control, vol. 55, no. 2, pp. 498–502, Feb. 2010.

[127]   S. Di Cairano and A. Bemporad, “Model predictive control tuning by controller matching,” IEEE Transactions on Automatic Control, vol. 55, no. 1, pp. 185–190, 2010.

[128]   A. Bemporad, D. Bernardini, F.A. Cuzzola, and A. Spinelli, “Optimization-based feedback control of flatness in a cold tandem rolling,” J. Process Control, vol. 20, pp. 396–407, 2010.

[129]   A. Bemporad, S. Di Cairano, E. Henriksson, and K. H. Johansson, “Hybrid model predictive control based on wireless sensor feedback: An experimental study,” Int. J. Robust Nonlinear Control, vol. 20, pp. 209–225, 2010.

[130]   A. Bemporad and D. Muñoz de la Peña, “Multiobjective model predictive control,” Automatica, vol. 45, pp. 2823–2830, 2009.

[131]   S. Di Cairano, A. Bemporad, and J. Júlvez, “Event-driven optimization-based control of hybrid systems with integral continuous-time dynamics,” Automatica, vol. 45, pp. 1243–1251, 2009.

[132]   A. Bemporad, G. Bianchini, and F. Brogi, “Passivity analysis and passification of discrete-time hybrid systems,” IEEE Transactions on Automatic Control, vol. 54, no. 4, pp. 1004–1009, 2008.

[133]   M. Baotić, F. Borrelli, A. Bemporad, and M. Morari, “Efficient on-line computation of constrained optimal control,” SIAM Journal on Control and Optimization, vol. 47, no. 5, pp. 2470–2489, 2008.

[134]   P. Menchinelli and A. Bemporad, “Hybrid model predictive control of a solar air conditioning plant,” European Journal of Control, vol. 14, no. 6, pp. 501–515, 2008.

[135]   A. Alessio, M. Lazar, A. Bemporad, and W.P.M.H. Heemels, “Squaring the circle: An algorithm for generating polyhedral invariant sets from ellipsoidal ones,” Automatica, vol. 43, pp. 2096–2103, Dec. 2007.

[136]   S. Di Cairano, A. Bemporad, I. Kolmanovsky, and D. Hrovat, “Model predictive control of magnetically actuated mass spring dampers for automotive applications,” Int. J. Control, vol. 80, no. 11, pp. 1701–1716, 2007.

[137]   G. Pannocchia and A. Bemporad, “Combined design of disturbance model and observer for offset-free model predictive control,” IEEE Transactions on Automatic Control, vol. 52, no. 6, pp. 1048–1053, 2007.

[138]   A. Bemporad and N. Giorgetti, “Logic-based methods for optimal control of hybrid systems,” IEEE Transactions on Automatic Control, vol. 51, no. 6, pp. 963–976, 2006.

[139]   A. Bemporad, D. Muñoz de la Peña, and P. Piazzesi, “Optimal control of investments for quality of supply improvement in electrical energy distribution networks,” Automatica, vol. 42, no. 8, pp. 1331–1336, 2006, Special issue on “Optimal Control Applications to Management Sciences”.

[140]   A. Bemporad and C. Filippi, “An algorithm for approximate multiparametric convex programming,” Computational Optimization and Applications, vol. 35, no. 1, pp. 87–108, Sept. 2006.

[141]   M. Lazar, W.P.M.H. Heemels, S. Weiland, and A. Bemporad, “Stabilizing model predictive control of hybrid systems,” IEEE Transactions on Automatic Control, vol. 51, no. 11, pp. 1813–1818, 2006.

[142]   N. Giorgetti, G. Ripaccioli, A. Bemporad, I.V. Kolmanovsky, and D. Hrovat, “Hybrid model predictive control of direct injection stratified charge engines,” IEEE/ASME Transactions on Mechatronics, vol. 11, no. 5, pp. 499–506, Aug. 2006.

[143]   D. Muñoz de la Peña, T. Alamo, A. Bemporad, and E.F. Camacho, “A decomposition algorithm for feedback min-max model predictive control,” IEEE Transactions on Automatic Control, vol. 51, no. 10, pp. 1688–1692, 2006.

[144]   D. Muñoz de la Peña, A. Bemporad, and C. Filippi, “Robust explicit MPC based on approximate multi-parametric convex programming,” IEEE Transactions on Automatic Control, vol. 51, no. 8, pp. 1399–1403, Aug. 2006.

[145]   N. Giorgetti, A. Bemporad, H.E. Tseng, and D. Hrovat, “Hybrid model predictive control application towards optimal semi-active suspension,” Int. J. Control, vol. 79, no. 5, pp. 521–533, 2006.

[146]   C. Seatzu, D. Corona, A. Giua, and A. Bemporad, “Optimal control of continuous-time switched affine systems,” IEEE Transactions on Automatic Control, vol. 51, no. 5, pp. 726–741, 2006.

[147]   A. Bemporad, A. Garulli, S. Paoletti, and A. Vicino, “A bounded-error approach to piecewise affine system identification,” IEEE Transactions on Automatic Control, vol. 50, no. 10, pp. 1567–1580, Oct. 2005.

[148]   A. Bemporad, “Efficient conversion of mixed logical dynamical systems into an equivalent piecewise affine form,” IEEE Transactions on Automatic Control, vol. 49, no. 5, pp. 832–838, 2004.

[149]   A. Bemporad, A. Teel, and L. Zaccarian, “Anti-windup synthesis via sampled-data piecewise affine optimal control,” Automatica, vol. 40, no. 4, pp. 549–562, 2004.

[150]   A. Bemporad, C. Filippi, and F.D. Torrisi, “Inner and outer approximation of polytopes using boxes,” Computational Geometry: Theory and Applications, vol. 27, no. 2, pp. 151–178, 2004.

[151]   F. Borrelli, A. Bemporad, M. Fodor, and D. Hrovat, “An MPC/hybrid system approach to traction control,” IEEE Transactions on Control Systems Technology, vol. 14, no. 3, pp. 541–552, May 2006.

[152]   F.D. Torrisi and A. Bemporad, “HYSDEL — A tool for generating computational hybrid models,” IEEE Transactions on Control Systems Technology, vol. 12, no. 2, pp. 235–249, Mar. 2004.

[153]   F. Borrelli, M. Baotić, A. Bemporad, and M. Morari, “Dynamic programming for constrained optimal control of discrete-time linear hybrid systems,” Automatica, vol. 41, no. 10, pp. 1709–1721, Oct. 2005.

[154]   J. Roll, A. Bemporad, and L. Ljung, “Identification of piecewise affine systems via mixed-integer programming,” Automatica, vol. 40, no. 1, pp. 37–50, 2004.

[155]   B. Potočnik, A. Bemporad, F.D. Torrisi, G. Mušič, and B. Zupančič, “Hysdel modelling and optimal control of a multi product batch plant,” Control Engineering Practice, vol. 12, no. 9, pp. 1127–1137, 2004.

[156]   A. Bemporad, F. Borrelli, and M. Morari, “Min-max control of constrained uncertain discrete-time linear systems,” IEEE Transactions on Automatic Control, vol. 48, no. 9, pp. 1600–1606, 2003.

[157]   A. Bemporad and C. Filippi, “Suboptimal explicit receding horizon control via approximate multiparametric quadratic programming,” Journal of Optimization Theory and Applications, vol. 117, no. 1, pp. 9–38, Apr. 2003.

[158]   P. Tøndel, T. A. Johansen, and A. Bemporad, “Evaluation of piecewise affine control via binary search tree,” Automatica, vol. 39, no. 5, pp. 945–950, May 2003.

[159]   P. Tøndel, T. A. Johansen, and A. Bemporad, “An algorithm for multi-parametric quadratic programming and explicit MPC solutions,” Automatica, vol. 39, no. 3, pp. 489–497, Mar. 2003.

[160]   F. Borrelli, A. Bemporad, and M. Morari, “A geometric algorithm for multi-parametric linear programming,” Journal of Optimization Theory and Applications, vol. 118, no. 3, pp. 515–540, Sept. 2003.

[161]   B. Potočnik, A. Bemporad, F.D. Torrisi, G. Mušič, and B. Zupančič, “Hybrid modeling and optimal control of an asphalt base process,” Elektrotehniški vestnik (Electrotechnical Review), vol. 70, no. 4, pp. 208–214, 2003.

[162]   A. Bemporad, F. Borrelli, and M. Morari, “Model predictive control based on linear programming — The explicit solution,” IEEE Transactions on Automatic Control, vol. 47, no. 12, pp. 1974–1985, 2002.

[163]   A. Bemporad, M. Morari, V. Dua, and E.N. Pistikopoulos, “The explicit linear quadratic regulator for constrained systems,” Automatica, vol. 38, no. 1, pp. 3–20, 2002.

[164]   A. Bemporad, M. Morari, V. Dua, and E.N. Pistikoupolos, “Corrigendum to: “The explicit linear quadratic regulator for constrained systems” [Automatica 38(1) (2002) 3–20],” 2003, vol. 39, pp. 1845–1846.

[165]   A. Bemporad, W.P.M.H. Heemels, and B. De Schutter, “On hybrid systems and closed-loop MPC systems,” IEEE Transactions on Automatic Control, vol. 47, no. 5, pp. 863–869, May 2002.

[166]   E.N. Pistikopoulos, V. Dua, N.A. Bozinis, A. Bemporad, and M. Morari, “On-line optimization via off-line parametric optimization tools,” Computers & Chemical Engineering, vol. 26, no. 2, pp. 175–185, Feb. 2002.

[167]   K. Asano, K. Tsuda, A. Bemporad, and M. Morari, “Predictive control for hybrid systems and its application to process control,” Systems, Control and Information, vol. 46, no. 3, pp. 110–119, 2002, (in Japanese).

[168]   A. Bemporad, F.D. Torrisi, and M. Morari, “Discrete-time hybrid modeling and verification of the batch evaporator process benchmark,” European Journal of Control, vol. 7, no. 4, pp. 382–399, July 2001.

[169]   W.P.M.H. Heemels, B. De Schutter, and A. Bemporad, “Equivalence of hybrid dynamical models,” Automatica, vol. 37, no. 7, pp. 1085–1091, July 2001.

[170]   B. De Schutter, W.P.M.H. Heemels, and A. Bemporad, “Note on the equivalence of linear complementarity problems,” Operations Research Letters, vol. 30, no. 4, pp. 211–222, Aug. 2002.

[171]   A. Bemporad, G. Ferrari-Trecate, and M. Morari, “Observability and controllability of piecewise affine and hybrid systems,” IEEE Transactions on Automatic Control, vol. 45, no. 10, pp. 1864–1876, 2000.

[172]   A. Bemporad, K. Fukuda, and F.D. Torrisi, “Convexity recognition of the union of polyhedra,” Computational Geometry: Theory and Applications, vol. 18, pp. 141–154, 2001.

[173]   A. Bemporad, M. Di Marco, and A. Tesi, “Sonar-based wall-following control of mobile robots,” ASME J. Dynamic Systems, Measurement & Control, vol. 122, pp. 226–230, Mar. 2000.

[174]   A. Bemporad and A. Garulli, “Output-feedback predictive control of constrained linear systems with disturbances via set-membership state estimation,” Int. J. Control, vol. 73, no. 8, pp. 655–665, 2000.

[175]   E.N. Pistikopoulos, V. Dua N.A. Bozinis, A. Bemporad, and M. Morari, “On-line optimization via off-line parametric optimization tools,” Computers & Chemical Engineering, vol. 24, no. 2-7, pp. 183–188, 2000.

[176]   A. Bemporad and M. Morari, “Control of systems integrating logic, dynamics, and constraints,” Automatica, vol. 35, no. 3, pp. 407–427, 1999.

[177]   A. Bemporad, T.J. Tarn, and N. Xi, “Predictive path parameterization for constrained robot control,” IEEE Trans. Control Systems Technology, vol. 7, no. 6, pp. 648–656, 1999.

[178]   M. Morari, A. Bemporad, and D. Mignone, “A framework for control, state estimation, fault detection, and verification of hybrid systems,” Automatisierungstechnik, vol. 47, pp. 374–381, 1999.

[179]   A. Bemporad, “Reference governor for constrained nonlinear systems,” IEEE Transactions on Automatic Control, vol. AC-43, no. 3, pp. 415–419, 1998.

[180]   A. Bemporad, “A predictive controller with artificial Lyapunov function for linear systems with input/state constraints,” Automatica, vol. 34, no. 10, pp. 1255–1260, 1998.

[181]   A. Bemporad and E. Mosca, “Fulfilling hard constraints in uncertain linear systems by reference managing,” Automatica, vol. 34, no. 4, pp. 451–461, 1998.

[182]   A. Bemporad, A. Casavola, and E. Mosca, “A predictive reference governor for constrained control systems,” Computers in Industry, vol. 36, pp. 55–64, 1998.

[183]   A. Bemporad, A. Casavola, and E. Mosca, “Nonlinear control of constrained linear systems via predictive reference management,” IEEE Transactions on Automatic Control, vol. AC-42, no. 3, pp. 340–349, 1997.

[184]   A. Bemporad and E. Mosca, “Filtraggio predittivo del riferimento per il controllo di sistemi vincolati,” Automazione e Strumentazione, vol. 43, pp. 117–123, 1995, In Italian.

[185]   A. Bemporad, L. Chisci, and E. Mosca, “On the stabilizing property of SIORHC,” Automatica, vol. 30, no. 12, pp. 2013–2015, 1994.

BOOK CHAPTERS

[186]   A. Molin, E. Aguilar, D. Nickovic, M. Zhu, A. Bemporad, and H. Esen, “Specification-guided critical scenario identification for automated driving,” in Formal Methods, Springer International Publishing, Ed., vol. 14000 of Lecture Notes in Computer Science, pp. 610–621. Cham, March 6–10 2023, Proc. 25th Int. Symp. Formal Methods, Lübeck, Germany.

[187]   M. Paggi, A. Bemporad, and J. Reinoso, “Computational methods for contact problems with roughness,” in Modeling and Simulation of Tribological Problems in Technology, M. Paggi and D. Hills, Eds., vol. 593 of CISM International Centre for Mechanical Sciences (Courses and Lectures), pp. 131–178. Springer-Verlag, 2020.

[188]   D. Piga, S. Formentin, R. Tóth, A. Bemporad, and S.M. Savaresi, “A hierarchical approach to data-driven LPV control design of constrained systems,” in Data-driven Filter and Control Design: Methods and Applications, C. Novara and S. Formentin, Eds., pp. 213–237. IET - Institution of Engineering & Technology, 2019.

[189]   A. Bemporad, “Explicit model predictive control,” in Encyclopedia of Systems and Control, J. Baillieul and T. Samad, Eds., pp. 744–751. Springer International Publishing, Cham, 2021.

[190]   M. Saponara, V. Barrena, A. Bemporad, E.N. Hartley, J. Maciejowski, A. Richards, A. Tramutola, and P. Trodden, “Model predictive control application to spacecraft rendezvous in Mars Sample & Return scenario,” in Progress in Flight Dynamics, GNC, and Avionics, vol. 6, pp. 137–158. 2013.

[191]   A. Bemporad and D. Barcelli, “Decentralized model predictive control,” in Networked Control Systems, A. Bemporad, W.P.M.H. Heemels, and M. Johansson, Eds., Lecture Notes in Control and Information Sciences, pp. 149–178. Springer-Verlag, Berlin Heidelberg, 2010.

[192]   S. Di Cairano, D. Yanakiev, A. Bemporad, I.V. Kolmanovsky, and D. Hrovat, “Model predictive powertrain control: An application to idle speed regulation,” in Automotive Model Predictive Control: Models, Methods and Applications, L. Del Re, F. Allgöwer, L. Glielmo, C. Guardiola, and I. Kolmanovsky, Eds., Linz, Austria, 2009, vol. 402 of Lecture notes in control and information sciences, pp. 183–194, Springer-Verlag.

[193]   A. Alessio and A. Bemporad, “A survey on explicit model predictive control,” in Nonlinear Model Predictive Control: Towards New Challenging Applications, D.M. Raimondo L. Magni, F. Allgower, Ed., Berlin Heidelberg, 2009, vol. 384 of Lecture Notes in Control and Information Sciences, pp. 345–369, Springer-Verlag.

[194]   D. Bernardini, D. Muñoz de la Peña, A. Bemporad, and E. Frazzoli, “Simultaneous optimal control and discrete stochastic sensor selection,” in Hybrid Systems: Computation and Control, R. Majumdar and P. Tabuada, Eds., number 5469 in Lecture Notes in Computer Science, pp. 61–75. Springer-Verlag, Berlin Heidelberg, 2009.

[195]   G. Ripaccioli, A. Bemporad, F. Assadian, C. Dextreit, S. Di Cairano, and I.V. Kolmanovsky, “Hybrid modeling, identification, and predictive control: an application to hybrid electric vehicle energy management,” in Hybrid Systems: Computation and Control, R. Majumdar and P. Tabuada, Eds., number 5469 in Lecture Notes in Computer Science, pp. 321–335. Springer-Verlag, Berlin Heidelberg, 2009.

[196]   A. Bemporad, M.K. Çamlibel, B. De Schutter, W.P.M.H. Heemels, A.J. van der Schaft, and J.M. Schumacher, “Chapter 5: Further switched systems,” in Handbook of Hybrid Systems Control: Theory, Tools, and Applications, J. Lunze and F. Lamnabhi-Lagarrigue, Eds., pp. 139–192. Cambridge University Press, 2009.

[197]   A. Bemporad, S. Di Cairano, G. Ferrari-Trecate, M. Kvasnica, M. Morari, and S. Paoletti, “Chapter 10: Tools for modeling, simulation, control, and verification of piecewise affine systems,” in Handbook of Hybrid Systems Control: Theory, Tools, and Applications, J. Lunze and F. Lamnabhi-Lagarrigue, Eds., pp. 297–324. Cambridge University Press, 2009.

[198]   L. Benvenuti, A. Balluchi, A. Bemporad, S. Di Cairano, B. Johansson, R. Johansson, A. Sangiovanni-Vincentelli, and P. Tunestål, “Chapter 15: Automotive control,” in Handbook of Hybrid Systems Control: Theory, Tools, and Applications, J. Lunze and F. Lamnabhi-Lagarrigue, Eds., pp. 439–469. Cambridge University Press, 2009.

[199]   S. Di Cairano, M. Lazar, A. Bemporad, and W.P.M.H. Heemels, “A control Lyapunov approach to predictive control of hybrid systems,” in Hybrid Systems: Computation and Control, M. Egerstedt and B. Mishra, Eds., number 4981 in Lecture Notes in Computer Science, pp. 130–143. Springer-Verlag, Berlin Heidelberg, 2008.

[200]   S. Di Cairano, K.H. Johansson, A. Bemporad, and R.M. Murray, “Dynamic network state estimation in networked control systems,” in Hybrid Systems: Computation and Control, M. Egerstedt and B. Mishra, Eds., number 4981 in Lecture Notes in Computer Science, pp. 144–157. Springer-Verlag, Berlin Heidelberg, 2008.

[201]   C. Ocampo-Martinez, A. Bemporad, A. Ingimundarson, and V. Puig, “On hybrid model predictive control of sewer networks,” in Identification and Control: The gap between theory & practice, R.S. Sánchez Peña, J. Quevedo Casín, and V. Puig, Eds., pp. 87–114. Springer-Verlag, London, 2007.

[202]   M. Lazar, W.P.M.H. Heemels, A. Bemporad, and S. Weiland, “Discrete-time non-smooth nonlinear MPC: Stability and robustness,” in Assessment and Future Directions of Nonlinear Model Predictive Control, R. Findeisen F. Allgower, L. Biegler, Ed., vol. 358 of Lecture Notes in Control and Information Sciences, pp. 93–103. Springer-Verlag, 2007.

[203]   A. Bemporad, S. Di Cairano, and J. Júlvez, “Event-based model predictive control and verification of integral continuous-time hybrid automata,” in Hybrid Systems: Computation and Control, J.P. Hespanha and A. Tiwari, Eds., number 3927 in Lecture Notes in Computer Science, pp. 93–107. Springer-Verlag, 2006.

[204]   A. Bemporad and S. Di Cairano, “Optimal control of discrete hybrid stochastic automata,” in Hybrid Systems: Computation and Control, M. Morari and L. Thiele, Eds., number 3414 in Lecture Notes in Computer Science, pp. 151–167. Springer-Verlag, 2005.

[205]   M. Lazar, W.P.M.H. Heemels, S. Weiland, A. Bemporad, and O. Pastravanu, “Infinity norms as Lyapunov functions for model predictive control of constrained PWA systems,” in Hybrid Systems: Computation and Control, M. Morari and L. Thiele, Eds., number 3414 in Lecture Notes in Computer Science, pp. 417–432. Springer-Verlag, 2005.

[206]   A. Bemporad and N. Giorgetti, “SAT-based branch & bound and optimal control of hybrid dynamical systems,” in Int. Conf. on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimisation Problems (CP-AI-OR), Nice, France, J.-C. Regin and M. Rueher, Eds., number 3011 in Lecture Notes in Computer Science, pp. 96–111. Springer-Verlag, Apr. 2004.

[207]   A. Bemporad and N. Giorgetti, “A SAT-based hybrid solver for optimal control of hybrid systems,” in Hybrid Systems: Computation and Control, R. Alur and G.J. Pappas, Eds., number 2993 in Lecture Notes in Computer Science, pp. 126–141. Springer-Verlag, 2004.

[208]   A. Bemporad, A. Garulli, S. Paoletti, and A. Vicino, “A greedy approach to identification of piecewise affine models,” in Hybrid Systems: Computation and Control, O. Maler and A. Pnueli, Eds. 2003, number 2623 in Lecture Notes in Computer Science, pp. 97–112, Springer-Verlag.

[209]   A. Bemporad, P. Borodani, and M. Mannelli, “Hybrid control of an automotive robotized gearbox for reduction of consumptions and emissions,” in Hybrid Systems: Computation and Control, O. Maler and A. Pnueli, Eds. 2003, number 2623 in Lecture Notes in Computer Science, pp. 81–96, Springer-Verlag.

[210]   A. Bemporad, F. Borrelli, and M. Morari, “On the optimal control law for linear discrete time hybrid systems,” in Hybrid Systems: Computation and Control, M. Greenstreet and C. Tomlin, Eds. 2002, number 2289 in Lecture Notes in Computer Science, pp. 105–119, Springer-Verlag.

[211]   F. Borrelli, A. Bemporad, M. Fodor, and D. Hrovat, “A hybrid approach to traction control,” in Hybrid Systems: Computation and Control, A. Sangiovanni-Vincentelli and M.D. Di Benedetto, Eds. 2001, number 2034 in Lecture Notes in Computer Science, pp. 162–174, Springer-Verlag.

[212]   A. Bemporad, F.D. Torrisi, and M. Morari, “Optimization-based verification and stability characterization of piecewise affine and hybrid systems,” in Hybrid Systems: Computation and Control, B. Krogh and N. Lynch, Eds. 2000, vol. 1790 of Lecture Notes in Computer Science, pp. 45–58, Springer-Verlag.

[213]   A. Bemporad and M. Morari, “Verification of hybrid systems via mathematical programming,” in Hybrid Systems: Computation and Control, F.W. Vaandrager and J.H. van Schuppen, Eds., vol. 1569 of Lecture Notes in Computer Science, pp. 31–45. Springer-Verlag, 1999.

[214]   A. Bemporad and M. Morari, “Robust model predictive control: A survey,” in Robustness in Identification and Control, A. Garulli, A. Tesi, and A. Vicino, Eds., number 245 in Lecture Notes in Control and Information Sciences, pp. 207–226. Springer-Verlag, 1999.

[215]   A. Bemporad and M. Morari, “Predictive control of constrained hybrid systems,” in Nonlinear Model Predictive Control, F. Allgower and A. Zheng, Eds., vol. 26 of Progress in Systems and Control Theory Series, pp. 71–98. Birkhauser Verlag, Basel, 2000.

CONFERENCE PAPERS

[216]   M. Mönnigmann, R. Hill, A. Bemporad, and G. Pannocchia, “Symbolic dynamics for active sets of a class of constrained nonlinear optimal control and MPC problems,” in IFAC Conference on Nonlinear Model Predictive Control, Kyoto, Japan, Aug. 2024.

[217]   K. Løwenstein, D. Bernardini, A. Bemporad, and L. Fagiano, “Physics-informed online learning by moving horizon estimation: Learning recurrent neural networks in gray-box models,” in IFAC Conference on Nonlinear Model Predictive Control, Kyoto, Japan, Aug. 2024.

[218]   M. Zhu, A. Bemporad, M. Kneissl, and H. Esen, “Learning critical scenarios in feedback control systems for automated driving,” in IEEE 26th Int. Conf. on Intelligent Transportation Systems, Bilbao, Bizkaia, Spain, Sept. 2023, also available on arXiv at https://arxiv.org/pdf/2209.12586.

[219]   L. Wu and A. Bemporad, “A construction-free coordinate-descent augmented-Lagrangian method for embedded linear MPC based on ARX models,” 2023, also available on https://arxiv.org/abs/2207.06098.

[220]   S. Menchetti, M. Zanon, and A. Bemporad, “Linear observer learning by temporal difference,” in Proc. 61th IEEE Conf. on Decision and Control, pp. 2777–2782. Cancún, Mexico, 2022.

[221]   M. Zhu, A. Bemporad, and D. Piga, “Preference-based MPC calibration,” in European Control Conference, 2021, also available on https://arxiv.org/pdf/2003.11294.pdf.

[222]   L. Ferrarotti, V. Breschi, and A. Bemporad, “The benefits of sharing: a cloud-aided performance-driven framework to learn optimal feedback policies,” in 3rd Annual Learning for Dynamics & Control Conference. Proceedings of Machine Learning Research, 2021, vol. 144, pp. 87–98.

[223]   S. Abdufattokhov, M. Zanon, and A. Bemporad, “Learning convex terminal costs for complexity reduction in MPC,” in Proc. 60th IEEE Conf. on Decision and Control, pp. 2163–2168. Austin, TX, USA, 2021.

[224]   V. Breschi, A. Bemporad, and I.V. Kolmanovsky, “An ADMM-based approach for multi-class recursive parameter estimation,” in Proc. 60th IEEE Conf. on Decision and Control, pp. 5169–5174. Austin, TX, USA, 2021.

[225]   L. Ferrarotti and A. Bemporad, “Learning nonlinear feedback controllers from data via optimal policy search and stochastic gradient descent,” in Proc. 59th IEEE Conf. on Decision and Control, Jeju Island, South Korea, 2020, pp. 4961–4966.

[226]   D. Masti, V. Breschi, S. Formentin, and A. Bemporad, “Direct data-driven design of neural reference governors,” in Proc. 59th IEEE Conf. on Decision and Control, Jeju Island, South Korea, 2020, pp. 4955–4960.

[227]   S. Mohamed, N. Saraf, D. Bernardini, D. Goswami, T. Basten, and A. Bemporad, “Adaptive predictive control for pipelined multiprocessor image-based control systems considering workload variations,” in Proc. 59th IEEE Conf. on Decision and Control, Jeju Island, South Korea, 2020, pp. 5236–5242.

[228]   V. Breschi, D. Masti, S. Formentin, and A. Bemporad, “NAW-NET: neural anti-windup control for saturated nonlinear systems,” in Proc. 59th IEEE Conf. on Decision and Control, Jeju Island, South Korea, 2020, pp. 3335–3340.

[229]   S. Simić, A. Bemporad, O. Inverso, and M. Tribastone, “Tight error analysis in fixed-point arithmetic,” in Proc. 26th Int. Conf. on integrated Formal Methods, Lugano, Switzerland, 2020.

[230]   V. Breschi, L. Ferrarotti, and A. Bemporad, “Cloud-based collaborative learning of optimal feedback controllers,” in Proc. 21th IFAC World Congress. IFAC-PapersOnLine, 2020, vol. 53, pp. 2660–2665.

[231]   L. Ferrarotti and A. Bemporad, “Learning optimal switching feedback controllers from data,” in Proc. 21th IFAC World Congress. IFAC-PapersOnLine, 2020, vol. 53, pp. 1602–1607.

[232]   S. Gros, M. Zanon, and A. Bemporad, “Safe reinforcement learning via projection on a safe set: How to achieve optimality?,” in Proc. 21th IFAC World Congress. IFAC-PapersOnLine, 2020, vol. 53, pp. 8076–8081.

[233]   P. Krupa, N. Saraf, D. Limon, and A. Bemporad, “PLC implementation of a real-time embedded MPC algorithm based on linear input/output models,” in Proc. 21th IFAC World Congress. IFAC-PapersOnLine, 2020, vol. 53, pp. 6987–6992.

[234]   S.K. Mulagaleti, M. Zanon, and A. Bemporad, “Dynamic output disturbance models for robust model predictive control,” in Proc. 21th IFAC World Congress. IFAC-PapersOnLine, 2020, vol. 53, pp. 7–12.

[235]   D. Masti, F. Smarra, A. D’Innocenzo, and A. Bemporad, “Learning affine predictors for MPC of nonlinear systems via artificial neural networks,” in Proc. 21th IFAC World Congress. IFAC-PapersOnLine, 2020, vol. 53, pp. 5233–5238.

[236]   D. Masti, T. Pippia, B. De Schutter, and A. Bemporad, “Learning approximate semi-explicit hybrid MPC with an application to microgrids,” in Proc. 21th IFAC World Congress. IFAC-PapersOnLine, 2020, vol. 53, pp. 5207–5212.

[237]   M. Forgione, D. Piga, and A. Bemporad, “Efficient calibration of embedded MPC,” in Proc. 21th IFAC World Congress. IFAC-PapersOnLine, 2020, vol. 53, pp. 5189–5194.

[238]   V. Breschi, D. Piga, and A. Bemporad, “Maximum-a-posteriori estimation of jump Box-Jenkins models,” in Proc. 58th IEEE Conf. on Decision and Control. Nice, France, 2019.

[239]   D. Piga, M. Forgione, S. Formentin, and A. Bemporad, “Performance-oriented model learning for data-driven MPC design,” in Proc. 58th IEEE Conf. on Decision and Control. Nice, France, 2019, also appeared in IEEE Control Systems Letters. See also https://arxiv.org/abs/1904.10839.

[240]   D. Masti, D. Bernardini, and A. Bemporad, “Learning virtual sensors for estimating the scheduling signal of parameter-varying systems,” in 27^th Mediterranean Conference on Control and Automation. Akko, Israel, 2019.

[241]   L. Ferrarotti and A. Bemporad, “Synthesis of feedback controllers from data via optimal policy search and stochastic gradient descent,” in Proc. European Control Conf., 2019, pp. 2486–2491.

[242]   M. Zanon, S. Gros, and A. Bemporad, “Practical reinforcement learning of stabilizing economic MPC,” in Proc. European Control Conf., 2019, pp. 2258–2263.

[243]   M. Mejari, D. Piga, R Tóth, and A. Bemporad, “Kernelized identification of linear parameter-varying models with linear fractional representation,” in Proc. European Control Conf., 2019, pp. 337–342.

[244]   D. Masti and A. Bemporad, “Learning explicit binary warm starts for multiparametric mixed-integer programming,” in Proc. European Control Conf., 2019, pp. 1494–1499.

[245]   N. Saraf, M. Zanon, and A. Bemporad, “A fast NMPC approach based on bounded-variable nonlinear least squares,” in 6th IFAC Conf. on Nonlinear Model Predictive Control, Madison, WI, 2018, pp. 414–419.

[246]   J.R. Salvador, D. Muñoz de la Peña, T. Alamo, and A. Bemporad, “Data-based predictive control via direct weight optimization,” in 6th IFAC Conf. on Nonlinear Model Predictive Control, Madison, WI, 2018, pp. 437–442.

[247]   A. Bemporad and V.V. Naik, “A numerically robust mixed-integer quadratic programming solver for embedded hybrid model predictive control,” in 6th IFAC Conf. on Nonlinear Model Predictive Control, Madison, WI, 2018, pp. 502–507.

[248]   P. Mercader, D. Rubin, H.-N. Nguyen, A. Bemporad, and P.-O. Gutman, “Simple interpolating control,” in 9th IFAC Symposium on Robust Control Design, vol. 51, pp. 42–47. Florianópolis, Brazil, 2018.

[249]   M. Mejari, V.V. Naik, D. Piga, and A. Bemporad, “Regularized moving-horizon PWA regression for LPV system identification,” in 18th IFAC Symposium on System Identification, vol. 51, pp. 1092–1097. Stockholm, Sweden, 2018.

[250]   V. Breschi, D. Piga, and A. Bemporad, “Jump model learning and filtering for energy end-use disaggregation,” in 18th IFAC Symposium on System Identification, vol. 51, pp. 275–280. Stockholm, Sweden, 2018.

[251]   D. Masti and A. Bemporad, “Learning nonlinear state-space models using deep autoencoders,” in Proc. 57th IEEE Conf. on Decision and Control, pp. 3862–3867. Miami Beach, FL, USA, 2018.

[252]   V. Breschi, A. Bemporad, D. Piga, and S. Boyd, “Prediction error methods in learning jump ARMAX models,” in Proc. 57th IEEE Conf. on Decision and Control, pp. 2247–2252. Miami Beach, FL, USA, 2018.

[253]   M. Mejari, V.V. Naik, D. Piga, and A. Bemporad, “Energy disaggregation using piecewise affine regression and binary quadratic programming,” in Proc. 57th IEEE Conf. on Decision and Control, pp. 3116–3121. Miami Beach, FL, USA, 2018.

[254]   V. Breschi, A. Bemporad, and D. Piga, “Kalman filtering for energy disaggregation,” in 1st IFAC Workshop on Integrated Assessment Modelling for Environmental Systems (IAMES 2018). 2018.

[255]   D. Selvi, D. Piga, and A. Bemporad, “Towards direct data-driven control design of optimal controllers,” in Proc. European Control Conf., Limassol, Cyprus, 2018, pp. 2836–2841.

[256]   B. Stellato, V.V. Naik, A. Bemporad, P.J. Goulart, and S. Boyd, “Embedded mixed-integer quadratic optimization using the OSQP solver,” in Proc. European Control Conf., 2018, pp. 1536–1541.

[257]   P. Latafat, A. Bemporad, and P. Patrinos, “Plug and play distributed model predictive control with dynamic coupling: A randomized primal-dual proximal algorithm,” in Proc. European Control Conf., 2018, pp. 1160–1165.

[258]   A. Bemporad, D. Bernardini, R. Long, and J. Verdejo, “Model predictive control of turbocharged gasoline engines for mass production,” in WCX^TM: SAE World Congress Experience, Detroit, MI, USA, Apr. 2018, [preview] [paper].

[259]   A. Bemporad, D. Bernardini, M. Livshiz, and B. Pattipati, “Supervisory model predictive control of a powertrain with a continuously variable transmission,” in WCX^TM: SAE World Congress Experience, Detroit, MI, USA, Apr. 2018, [preview] [paper].

[260]   V. Breschi, I.V. Kolmanovsky, and A. Bemporad, “Cloud-aided collaborative estimation by ADMM-RLS algorithms for connected vehicle prognostics,” in Proc. American Contr. Conf., Milwaukee, WI, 2018, pp. 2727–2732.

[261]   R.A.E. Zidek, I.V. Kolmanovsky, and A. Bemporad, “Stochastic MPC approach to drift counteraction,” in Proc. American Contr. Conf., Milwaukee, WI, 2018, pp. 721–727.

[262]   O. Inverso, A. Bemporad, and M. Tribastone, “SAT-based synthesis of spoofing attacks in cyber-physical control systems,” in 9th ACM/IEEE International Conference on Cyber-Physical Systems, 2018.

[263]   G. Banjac, B. Stellato, N. Moehle, P. Goulart, A. Bemporad, and S. Boyd, “Embedded code generation using the OSQP solver,” in Proc. 56th IEEE Conf. on Decision and Control, Melbourne, Australia, 2017, pp. 1906–1911, https://github.com/oxfordcontrol/osqp.

[264]   N. Saraf and A. Bemporad, “Fast model predictive control based on linear input/output models and bounded-variable least squares,” in Proc. 56th IEEE Conf. on Decision and Control, Melbourne, Australia, 2017.

[265]   M. Graf Plessen, P.F. Lima, J. Mårtensson, A. Bemporad, and B. Wahlberg, “Trajectory planning under vehicle dimension constraints using sequential linear programming,” in Proc. 20th Int. Conf. Intelligent Transportation Systems, 2017.

[266]   V.V. Naik and A. Bemporad, “Embedded mixed-integer quadratic optimization using accelerated dual gradient projection,” in Proc. 20th IFAC World Congress, Toulouse, France, July 2017, vol. 50, pp. 10723–10728.

[267]   M. Mejari, D. Piga, and A. Bemporad, “LPV model-order selection from noise-corrupted output and scheduling signal measurements,” in Proc. 20th IFAC World Congress, Toulouse, France, July 2017, vol. 50, pp. 8685–8690.

[268]   P. Sopasakis, D. Herceg, P. Patrinos, and A. Bemporad, “Stochastic economic model predictive control for Markovian switching systems,” in Proc. 20th IFAC World Congress, Toulouse, France, July 2017, vol. 50, pp. 524–530.

[269]   A.K. Sampathirao, P. Sopasakis, A. Bemporad, and P. Patrinos, “Proximal limited-memory quasi-Newton methods for scenario-based stochastic optimal control,” in Proc. 20th IFAC World Congress, Toulouse, France, July 2017, vol. 50, pp. 11865–11870.

[270]   M. Graf Plessen and A. Bemporad, “Parallel investments in multiple call and put options for the tracking of desired profit profiles,” in Proc. American Contr. Conf., Seattle, WA, 2017.

[271]   R.A.E. Zidek, A. Bemporad, and I.V. Kolmanovsky, “Optimal and receding horizon drift counteraction control: Linear programming approaches,” in Proc. American Contr. Conf., Seattle, WA, 2017, pp. 2636–2641.

[272]   R.A.E. Zidek, I.V. Kolmanovsky, C. Petersen, and A. Bemporad, “Receding horizon drift counteraction and its application to spacecraft attitude control,” in 27th AAS/AIAA Space Flight Mechanics Meeting, San Antonio, TX, 2017.

[273]   V.V. Naik, M. Mejari, D. Piga, and A. Bemporad, “Regularized moving-horizon PWA regression using mixed-integer quadratic programming,” in 25th Mediterranean Control Conference, Valletta, Malta, July 2017, pp. 1349–1354.

[274]    D. Herceg, G. Georgoulas, P. Sopasakis, M. Castaño Arranz, P. Patrinos, A. Bemporad, J. Niemi, and G. Nikolakopoulos, “Data-driven modelling, learning and stochastic predictive control for the steel industry,” in 25th Mediterranean Control Conference, Valletta, Malta, July 2017, pp. 1361–1366.

[275]   M. Graf Plessen and A. Bemporad, “Shortest path computations under trajectory constraints for ground vehicles within agricultural fields,” in 19th IEEE Intelligent Transportation Systems Conference, pp. 1733–1738. Rio de Janeiro, Brazil, 2016.

[276]   M. Graf Plessen, D. Bernardini, H. Esen, and A. Bemporad, “Multi-automated vehicle coordination using decoupled prioritized path planning for multi-lane one- and bi-directional traffic flow control,” in Proc. 55th IEEE Conf. on Decision and Control, Las Vegas, NV, 2016, pp. 1582–1588.

[277]   V. Breschi, D. Piga, and A. Bemporad, “Learning hybrid models with logical and continuous dynamics via multiclass linear separation,” in Proc. 55th IEEE Conf. on Decision and Control, Las Vegas, NV, 2016, pp. 353–358.

[278]   V. Breschi, A. Bemporad, and D. Piga, “Identification of hybrid and linear parameter varying models via recursive piecewise affine regression and discrimination,” in Proc. European Control Conf., Aalborg, Denmark, 2016.

[279]   M. Mejari, D. Piga, and A. Bemporad, “Regularized least square support vector machines for order and structure selection of LPV-ARX models,” in Proc. European Control Conf., Aalborg, Denmark, 2016.

[280]   A. Themelis, S. Villa, P. Patrinos, and A. Bemporad, “Stochastic gradient methods for stochastic model predictive control,” in Proc. European Control Conf., Aalborg, Denmark, 2016.

[281]   R. Takapoui, N. Moehle, S. Boyd, and A. Bemporad, “A simple effective heuristic for embedded mixed-integer quadratic programming,” in Proc. American Contr. Conf., Boston, MA, 2016, pp. 5619–5625.

[282]   A.K. Sampathirao, P. Sopasakis, A. Bemporad, and P. Patrinos, “Distributed solution of stochastic optimal control problems on GPUs,” in Proc. 54th IEEE Conf. on Decision and Control, Osaka, Japan, 2015, pp. 7183–7188.

[283]   C.A. Hans, P. Sopasakis, A. Bemporad, J. Raisch, and C. Collon, “Scenario-based model predictive operation control of islanded microgrids,” in Proc. 54th IEEE Conf. on Decision and Control, Osaka, Japan, 2015, pp. 3272–3277.

[284]   A. Bemporad, “Solving mixed-integer quadratic programs via nonnegative least squares,” in 5th IFAC Conf. on Nonlinear Model Predictive Control, Sevilla, Spain, 2015, pp. 73–79.

[285]   P. Sopasakis, D. Bernardini, H. Strauch, and A. Bemporad, “A hybrid model predictive control approach to attitude control with minimum-impulse-bit thrusters,” in Proc. European Control Conf., Linz, Austria, 2015.

[286]   P. Sopasakis, D. Bernardini, H. Strauch, S. Bennani, and A. Bemporad, “Sloshing-aware attitude control of impulsively actuated spacecraft,” in Proc. European Control Conf., Linz, Austria, 2015.

[287]   C.A. Pascucci, S. Bennani, and A. Bemporad, “Model predictive control for powered descent guidance and control,” in Proc. European Control Conf., Linz, Austria, 2015.

[288]   A. Guiggiani, I.V. Kolmanovsky, P. Patrinos, and A. Bemporad, “Constrained model predictive control of spacecraft attitude with reaction wheels desaturation,” in Proc. European Control Conf., Linz, Austria, 2015.

[289]   A. Guiggiani, I.V. Kolmanovsky, P. Patrinos, and A. Bemporad, “Fixed-point constrained model predictive control of spacecraft attitude,” in Proc. American Contr. Conf., Chicago, IL, 2015, pp. 2317–2322, http://arxiv.org/abs/1411.0479.

[290]   G. Gnecco, A. Bemporad, M. Gori, R. Morisi, and M. Sanguineti, “Online learning as an LQG optimal control problem with random matrices,” in Proc. European Control Conf., Linz, Austria, 2015.

[291]   G. Cimini, D. Bernardini, A. Bemporad, and S. Levijoki, “Online model predictive torque control for permanent magnet synchronous motors,” in 2015 IEEE Int. Conf. on Industrial Technology, pp. 2308–2313. Seville, Spain, Mar. 2015.

[292]   A. Khakimova, A. Shamshimova, D. Sharipova, A. Kusataeva, V. Ten, A. Bemporad, Y. Familiant, A. Shintemirov, and M. Rubagotti, “Modeling and hybrid model predictive control of a smart house,” in 15th IEEE Int. Conf. on Environment and Electrical Engineering, Rome, Italy, 2015, pp. 513–518.

[293]   H. Esen, M. Adachi, D. Bernardini, A. Bemporad, D. Rost, and J. Knodel, “Control as a service (CaaS). Cloud-based software architecture for automotive control applications,” in 2nd Int. Workshop on the Swarm at the Edge of the Cloud (SWEC), Seattle, WA, 2015.

[294]   G. Cimini, A. Bemporad, G. Ippoliti, and S. Longhi, “FRAM evaluation as unified memory for convex optimization algorithms,” in 6th European Embedded Design in Education and Research Conference, pp. 187–191. Milano, Italy, 2014.

[295]   H. Esen, T. Tashiro, D. Bernardini, and A. Bemporad, “Cabin heat thermal management in hybrid vehicles using model predictive control,” in 22nd Mediterranean Control Conference, Palermo, Italy, 2014.

[296]   I. Necoara, D.N. Clipici, P. Patrinos, and A. Bemporad, “MPC for power systems dispatch based on stochastic optimization,” in Proc. 19th IFAC World Congress, Cape Town, South Africa, 2014.

[297]   A.K. Sampathirao, J.M Grosso, P. Sopasakis, C. Ocampo-Martinez, A. Bemporad, and V. Puig, “Water demand forecasting for the optimal operation of large-scale drinking water networks: The Barcelona case study,” in Proc. 19th IFAC World Congress, Cape Town, South Africa, 2014.

[298]   A. Guiggiani, P. Patrinos, and A. Bemporad, “Fixed-point implementation of a proximal Newton method for embedded model predictive control,” in Proc. 19th IFAC World Congress, Cape Town, South Africa, 2014.

[299]   G. Gnecco, R. Morisi, and A. Bemporad, “Sparse solutions to the average consensus problem via ℓ₁-norm regularization of the fastest mixing Markov-chain problem,” in Proc. 53rd IEEE Conf. on Decision and Control, Los Angeles, CA, 2014, pp. 2228–2233.

[300]   P. Patrinos, L. Stella, and A. Bemporad, “Douglas-Rachford splitting: Complexity estimates and accelerated variants,” in Proc. 53rd IEEE Conf. on Decision and Control, Los Angeles, CA, 2014, pp. 4234–4239.

[301]   C.A. Pascucci, A. Bemporad, S. Bennani, and M. Rotunno, “Embedded MPC for space applications,” in 2nd IAA Conference on Dynamics and Control of Space Systems, 2014.

[302]   P. Patrinos and A. Bemporad, “Proximal Newton methods for convex composite optimization,” in Proc. 52nd IEEE Conf. on Decision and Control, Florence, Italy, 2013, pp. 2358–2363.

[303]   P. Sopasakis, D. Bernardini, and A. Bemporad, “Constrained model predictive control based on reduced-order models,” in Proc. 52nd IEEE Conf. on Decision and Control, Florence, Italy, 2013, pp. 7071–7076.

[304]   P. Patrinos, A. Guiggiani, and A. Bemporad, “Fixed-point dual gradient projection for embedded model predictive control,” in Proc. European Control Conf., Zürich, Switzerland, 2013, pp. 3602–3607.

[305]   M. Rubagotti, P. Patrinos, and A. Bemporad, “Stabilizing embedded MPC with computational complexity guarantees,” in Proc. European Control Conf., Zürich, CH, 2013, pp. 3065–3070.

[306]   L. Puglia, P. Patrinos, D. Bernardini, and A. Bemporad, “Reliability and efficiency for market parties in power systems,” in 10th International Conference on the European Energy Market (EEM13), Stockholm, Sweden, 2013.

[307]   L. Puglia, A. Bemporad, A. Virag, and A. Jokic, “A stochastic optimization approach to optimal bidding on Dutch ancillary services markets,” in 10th International Conference on the European Energy Market (EEM13), Stockholm, Sweden, 2013.

[308]   S. Di Cairano, W.P.M.H. Heemels, M. Lazar, and A. Bemporad, “Hybrid control Lyapunov functions for stabilization of hybrid systems,” in Hybrid Systems: Computation and Control, Philadelphia, USA, 2013, pp. 73–82.

[309]   R. Krenn, A. Gibbesch, G. Binet, and A. Bemporad, “Model predictive traction and steering control of planetary rovers,” in Proc. 12th Symposium on Advanced Space Technologies in Automation and Robotics (ASTRA), 2013.

[310]   P. Patrinos and A. Bemporad, “An accelerated dual gradient-projection algorithm for linear model predictive control,” in Proc. 51st IEEE Conf. on Decision and Control, Maui, HI, 2012, pp. 662–667.

[311]   P. Sopasakis, P. Patrinos, H. Sarimveis, and A. Bemporad, “Model predictive control for linear impulsive systems,” in Proc. 51st IEEE Conf. on Decision and Control, Maui, HI, 2012, pp. 5164–5169.

[312]   M. Rubagotti, T. Poggi, A. Bemporad, and M. Storace, “Piecewise affine direct virtual sensors with reduced complexity,” in Proc. 51st IEEE Conf. on Decision and Control, Maui, HI, 2012, pp. 4235–4240.

[313]   M. Rubagotti, L. Zaccarian, and A. Bemporad, “Stability analysis of discrete-time piecewise-affine systems over non-invariant domains,” in Proc. 51st IEEE Conf. on Decision and Control, Maui, HI, 2012, pp. 656–661.

[314]   V. Milić, S. Di Cairano, J. Kasac, A. Bemporad, and Z. Situm, “A numerical algorithm for nonlinear L2-gain optimal control with application to vehicle yaw stability control,” in Proc. 51st IEEE Conf. on Decision and Control, Maui, HI, 2012, pp. 5040–5045.

[315]   S. Di Cairano, C.A. Pascucci, and A. Bemporad, “The rendezvous dynamics under linear quadratic optimal control,” in Proc. 51st IEEE Conf. on Decision and Control, Maui, HI, 2012, pp. 6554–6559.

[316]   A. Bemporad and P. Patrinos, “Simple and certifiable quadratic programming algorithms for embedded linear model predictive control,” in Proc. 4th IFAC Nonlinear Model Predictive Control Conference, F. Allgower M. Lazar, Ed., 2012, pp. 14–20.

[317]   M. Rubagotti, D. Barcelli, and A. Bemporad, “Approximate explicit MPC on simplicial partitions for stabilization of constrained linear systems,” in Proc. 4th IFAC Nonlinear Model Predictive Control Conference, F. Allgower M. Lazar, Ed., 2012, pp. 119–125.

[318]   A. Oliveri, D. Barcelli, A. Bemporad, B. Genuit, W.P.M.H. Heemels, T. Poggi, M. Rubagotti, and M. Storace, “MOBY-DIC: A MATLAB toolbox for circuit-oriented design of explicit MPC,” in Proc. 4th IFAC Nonlinear Model Predictive Control Conference, F. Allgower M. Lazar, Ed., 2012, pp. 218–225.

[319]   G. Binet, R. Krenn, and A. Bemporad, “Model predictive control applications for planetary rovers,” in 11th Int. Symposium on Artificial Intelligence, Robotics and Automation in Space (iSAIRAS), Turin, Italy, 2012.

[320]   V. Milić, A. Bemporad, J. Kasac, and Z. Situm, “Numerical algorithm for nonlinear state feedback H-infinity optimal control problem,” in 20th Mediterranean Conference on Control and Automation, Barcelona, Spain, 2012, pp. 1253–1258.

[321]   P. Patrinos, D. Bernardini, A. Maffei, A. Jokic, and A. Bemporad, “Two-time-scale MPC for economically optimal real-time operation of balance responsible parties,” in IFAC 8th Power Plant and Power Systems Control Symposium, Tolouse, France, 2012, pp. 741–746.

[322]   A. Bemporad and C. Rocchi, “Decentralized linear time-varying model predictive control of a formation of unmanned aerial vehicles,” in Proc. 50th IEEE Conf. on Decision and Control and European Control Conf., Orlando, FL, 2011, pp. 7488–7493.

[323]   P. Patrinos, S. Trimboli, and A. Bemporad, “Stochastic MPC for real-time market-based optimal power dispatch,” in Proc. 50th IEEE Conf. on Decision and Control and European Control Conf., Orlando, FL, 2011, pp. 7111–7116.

[324]   S. Trimboli, M. Rubagotti, and A. Bemporad, “Stability and invariance analysis of uncertain PWA systems based on linear programming,” in Proc. 50th IEEE Conf. on Decision and Control and European Control Conf., Orlando, FL, 2011, pp. 7398–7403.

[325]   W.P.M.H. Heemels and A. Bemporad, “An upper Riemann-Stieltjes approach to stochastic design problems,” in Proc. 50th IEEE Conf. on Decision and Control and European Control Conf., Orlando, FL, 2011, pp. 2871–2876.

[326]   L. Puglia, D. Bernardini, and A. Bemporad, “A multi-stage stochastic optimization approach to optimal bidding on energy markets,” in Proc. 50th IEEE Conf. on Decision and Control and European Control Conf., Orlando, FL, 2011, pp. 1509–1514.

[327]   L. Liang, W.P.M.H. Heemels, and A. Bemporad, “Synthesis of low-complexity stabilizing piecewise affine controllers: A control-Lyapunov function approach,” in Proc. 50th IEEE Conf. on Decision and Control and European Control Conf., Orlando, FL, 2011, pp. 1227–1232.

[328]   M. Saponara, V. Barrena, A. Bemporad, E.N. Hartley, J. Maciejowski, A. Richards, A. Tramutola, and P. Trodden, “Model predictive control application to spacecraft rendezvous in Mars Sample & Return scenario,” in Proc. 4th European Conference for Aerospace Sciences (EUCASS), Saint Petersburg, Russia, 2011.

[329]   A. Bemporad, L. Puglia, and T. Gabbriellini, “A stochastic model predictive control approach to dynamic option hedging with transaction costs,” in Proc. American Contr. Conf., San Francisco, CA, USA, 2011, pp. 3862–3867.

[330]   T. Jorge, J.M. Lemos, M. Barao, and A. Bemporad, “Hybrid dynamic optimization for cruise speeed control,” in Proc. 18th IFAC World Congress, Milano, Italy, 2011, pp. 5082–5087.

[331]   D. Barcelli, A. Bemporad, and G. Ripaccioli, “Decentralized hierarchical multi-rate control of constrained linear systems,” in Proc. 18th IFAC World Congress, Milano, Italy, 2011, pp. 277–283.

[332]   T. Poggi, S. Trimboli, A. Bemporad, and M. Storace, “Explicit hybrid model predictive control: discontinuous piecewise-affine approximation and FPGA implementation,” in Proc. 18th IFAC World Congress, Milano, Italy, 2011, pp. 1350–1355.

[333]   A. Bemporad and C. Rocchi, “Decentralized hybrid model predictive control of a formation of unmanned aerial vehicles,” in Proc. 18th IFAC World Congress, Milano, Italy, 2011, pp. 11900–11906.

[334]   M. Rubagotti, S. Trimboli, D. Bernardini, and A. Bemporad, “Stability and invariance analysis of approximate explicit MPC based on PWA Lyapunov functions,” in Proc. 18th IFAC World Congress, Milano, Italy, 2011, pp. 5712–5717.

[335]   A. Bemporad, T. Gabbriellini, L. Puglia, and L. Bellucci, “Scenario-based stochastic model predictive control for dynamic option hedging,” in Proc. 49th IEEE Conf. on Decision and Control, Atlanta, GA, USA, 2010, pp. 6089–6094.

[336]   M. Bichi, G. Ripaccioli, S. Di Cairano, D. Bernardini, A. Bemporad, and I.V. Kolmanovsky, “Stochastic model predictive control with driver behavior learning for improved powertrain control,” in Proc. 49th IEEE Conf. on Decision and Control, Atlanta, GA, USA, 2010, pp. 6077–6082.

[337]   A. Bemporad, A. Oliveri, T. Poggi, and M. Storace, “Synthesis of stabilizing model predictive controllers via canonical piecewise affine approximations,” in Proc. 49th IEEE Conf. on Decision and Control, Atlanta, GA, USA, 2010, pp. 5296–5301.

[338]   D. Barcelli, A. Bemporad, and G. Ripaccioli, “Hierarchical multi-rate control design for constrained linear systems,” in Proc. 49th IEEE Conf. on Decision and Control, Atlanta, GA, USA, 2010, pp. 5216–5221.

[339]   D. Barcelli, D. Bernardini, and A. Bemporad, “Synthesis of networked switching linear decentralized controllers,” in Proc. 49th IEEE Conf. on Decision and Control, Atlanta, GA, USA, 2010, pp. 2480–2485.

[340]   D. Bernardini, T. Donkers, A. Bemporad, and W.P.M.H. Heemels, “A model predictive control approach for stochastic networked control systems,” in 2^nd IFAC Workshop on Distributed Estimation and Control in Networked Systems, Annecy, France, 2010, pp. 7–12.

[341]   S. Di Cairano, H.E. Tseng, D. Bernardini, and A. Bemporad, “Steering vehicle control by switched model predictive control,” in 6th IFAC Symposium Advances in Automotive Control, Münich, Germany, 2010.

[342]   A. Bemporad, W.P.M.H. Heemels, and M. Lazar, “On the synthesis of piecewise affine control laws,” in IEEE Int. Symposium on Circuits and Systems, Paris, France, 2010.

[343]   G. Ripaccioli, D. Bernardini, S. Di Cairano, A. Bemporad, and I.V. Kolmanovsky, “A stochastic model predictive control approach for series hybrid electric vehicle power management,” in Proc. American Contr. Conf., Baltimore, MD, 2010, pp. 5844–5849.

[344]   T. Donkers, W.P.M.H. Heemels, D. Bernardini, A. Bemporad, and V. Shneer, “Stability analysis of stochastic networked control systems,” in Proc. American Contr. Conf., Baltimore, MD, 2010, pp. 547–555.

[345]   D. Barcelli, C. Ocampo-Martinez, V. Puig, and A. Bemporad, “Decentralized model predictive control of drinking water networks using an automatic subsystem decomposition approach,” in 12th Symposium on Large-Scale Systems: Theory and Applications, Villeneuve d’Ascq, France, 2010.

[346]   D. Bernardini and A. Bemporad, “Scenario-based model predictive control of stochastic constrained linear systems,” in Proc. 48th IEEE Conf. on Decision and Control, Shanghai, China, 2009, pp. 6333–6338.

[347]   D. Bernardini, S. Di Cairano, A. Bemporad, and H.E. Tseng, “Drive-by-wire vehicle stabilization and yaw regulation: A hybrid model predictive control design,” in Proc. 48th IEEE Conf. on Decision and Control, Shanghai, China, 2009, pp. 7621–7626.

[348]   D. Barcelli and A. Bemporad, “Decentralized model predictive control of dynamically-coupled linear systems: Tracking under packet loss,” in 1st IFAC Workshop on Estimation and Control of Networked Systems, Venice, Italy, 2009, pp. 204–209.

[349]   A. Bemporad, C.A. Pascucci, and C. Rocchi, “Hierarchical and hybrid model predictive control of quadcopter air vehicles,” in 3rd IFAC Conference on Analysis and Design of Hybrid Systems, Zaragoza, Spain, 2009, pp. 14–19.

[350]   S. Trimboli, S. Di Cairano, A. Bemporad, and I.V. Kolmanovsky, “Model predictive control for systems with time delay: An application to air-fuel ratio control in automotive engines,” in 8th IFAC Workshop on Time Delay Systems, 2009.

[351]   S. Di Cairano and A. Bemporad, “Model predictive controller matching: Can MPC enjoy small signal properties of my favorite linear controller ?,” in Proc. European Control Conf., 2009, pp. 2217–2222.

[352]   A. Bemporad and D. Muñoz de la Peña, “Multiobjective model predictive control based on convex piecewise affine costs,” in Proc. European Control Conf., 2009, pp. 2402–2407.

[353]   D. Bernardini and A. Bemporad, “Energy-aware robust model predictive control with feedback from multiple noisy wireless sensors,” in Proc. European Control Conf., 2009, pp. 4308–4313.

[354]   A. Bemporad, “Modeling and control of hybrid dynamical systems: The Hybrid Toolbox for MATLAB,” in Proc. MATHMOD Conference, I. Troch and F. Breitenecker, Eds., number 35 in ARGESIM Reports, pp. 82–100. Vienna, Austria, 2009.

[355]   D. Bernardini and A. Bemporad, “Energy-aware robust model predictive control based on wireless sensor feedback,” in Proc. 47th IEEE Conf. on Decision and Control, Cancun, Mexico, 2008, pp. 3342–3347.

[356]   S. Di Cairano, D. Yanakiev, A. Bemporad, I.V. Kolmanovsky, and D. Hrovat, “An MPC design flow for automotive control and applications to idle speed regulation,” in Proc. 47th IEEE Conf. on Decision and Control, Cancun, Mexico, 2008, pp. 5686–5691.

[357]   A. Damoiseaux, A. Jokic, M. Lazar, P.P.J. van den Bosch, I.A. Hiskens, A. Alessio, and A. Bemporad, “Assessment of decentralized model predictive control techniques for power networks,” in 16th Power Systems Computation Conference, Glasgow, Scotland, 2008.

[358]   S. Di Cairano, A. Pasini, A. Bemporad, and R.M. Murray, “Convergence properties of dynamic agents consensus networks with broken links,” in Proc. American Contr. Conf., Seattle, WA, 2008, pp. 1362–1367.

[359]   A. Alessio and A. Bemporad, “Stability conditions for decentralized model predictive control under packet dropout,” in Proc. American Contr. Conf., Seattle, WA, 2008, pp. 3577–3582.

[360]   A. Ingimundarson, C. Ocampo-Martinez, A. Bemporad, and V. Puig, “Suboptimal hybrid model predictive control: Application to sewer networks,” in Proc. 17th IFAC World Congress, Seoul, Corea, 2008.

[361]   A. Bemporad, S. Di Cairano, E. Henriksson, and K. H. Johansson, “Hybrid model predictive control based on wireless sensor feedback: An experimental study,” in Proc. 46th IEEE Conf. on Decision and Control, New Orleans, LA, 2007, pp. 5062–5067.

[362]   A. Julius, M.S. Sakar, A. Bemporad, and G. J. Pappas, “Hybrid model predictive control of induction of Escherichia Coli,” in Proc. 46th IEEE Conf. on Decision and Control, New Orleans, LA, 2007, pp. 3913–3918.

[363]   A. Bemporad, S. Di Cairano, I. V. Kolmanovsky, and D. Hrovat, “Hybrid modeling and control of a multibody magnetic actuator for automotive applications,” in Proc. 46th IEEE Conf. on Decision and Control, New Orleans, LA, 2007, pp. 5270–5275.

[364]   A. Ingimundarson, C. Ocampo-Martinez, and A. Bemporad, “Model predictive control of hybrid systems based on mode-switching constraints,” in Proc. 46th IEEE Conf. on Decision and Control, New Orleans, LA, 2007, pp. 5265–5269.

[365]   A. Alessio and A. Bemporad, “Decentralized model predictive control of constrained linear systems,” in Proc. European Control Conf., Kos, Greece, 2007, pp. 2813–2818.

[366]   S. Di Cairano, A. Bemporad, and A. Caldelli, “Moving target detection and tracking in wireless sensor networks,” in Proc. European Control Conf., Kos, Greece, 2007, pp. 2218–2223.

[367]   S. Di Cairano, A. Bemporad, I. Kolmanovsky, and D. Hrovat, “Model predictive control of magnetic automotive actuators,” in Proc. American Contr. Conf., New York, NY, 2007, pp. 5082–5087.

[368]   A. Bemporad, F. Gentile, A. Mecocci, F. Molendi, and F. Rossi, “A wireless magneto-resistive sensor network for real-time vehicle detection,” in Proc. European Wireless Sensor Network Conf., Delft, The Netherlands, 2007, pp. 13–14, TR PDS-2007-001, TU/Delft.

[369]   A. Bemporad, “Model-based predictive control design: New trends and tools,” in Proc. 45th IEEE Conf. on Decision and Control, San Diego, CA, 2006, pp. 6678–6683.

[370]   A. Alessio, A. Bemporad, M. Lazar, and W.P.M.H. Heemels, “An algorithm for the computation of polyhedral invariant sets for closed-loop linear MPC systems,” in Proc. 45th IEEE Conf. on Decision and Control, San Diego, CA, 2006, pp. 4532–4537.

[371]   S. Di Cairano and A. Bemporad, “An equivalence result between linear hybrid automata and piecewise affine systems,” in Proc. 45th IEEE Conf. on Decision and Control, San Diego, CA, 2006, pp. 2631–2636.

[372]   A. Bemporad, “Optimization-based control of hybrid dynamical systems,” in Proc. 7th Portuguese Conference on Automatic Control (CONTROLO’06), Lisbon, Portugal, 2006, Plenary lecture.

[373]   A. Alessio and A. Bemporad, “Feasible mode enumeration and cost comparison for explicit quadratic model predictive control of hybrid systems,” in 2nd IFAC Conference on Analysis and Design of Hybrid Systems, Alghero, Italy, 2006, pp. 302–308.

[374]   S. Di Cairano, A. Bemporad, I. Kolmanovsky, and D. Hrovat, “Model predictive control of nonlinear mechatronic systems: An application to a magnetically actuated mass spring damper,” in 2nd IFAC Conference on Analysis and Design of Hybrid Systems, Alghero, Italy, 2006, pp. 241–246.

[375]   A. Alessio, M. Lazar, A. Bemporad, and W.P.M.H. Heemels, “Squaring the circle: An algorithm for generating polyhedral invariant sets from ellipsoidal ones,” in Proc. American Contr. Conf., Minneapolis, MN, 2006, pp. 3007–3012.

[376]   D. Muñoz de la Peña, T. Alamo, A. Bemporad, and E.F. Camacho, “Feedback min-max model predictive control based on a quadratic cost function,” in Proc. American Contr. Conf., Minneapolis, MN, 2006, pp. 1575–1680.

[377]   A. Bemporad, S. Di Cairano, and J. Júlvez, “Event-driven optimal control of integral continuous-time hybrid automata,” in Proc. 44th IEEE Conf. on Decision and Control and European Control Conf., Sevilla, Spain, 2005, pp. 1409–1414.

[378]   A. Bemporad, G. Bianchini, F. Brogi, and G. Chesi, “Passivity analysis of discrete-time hybrid systems using piecewise polynomial storage functions,” in Proc. 44th IEEE Conf. on Decision and Control and European Control Conf., Sevilla, Spain, 2005, pp. 5421–5426.

[379]   D. Muñoz de la Peña, A. Bemporad, and T. Alamo, “Stochastic programming applied to model predictive control,” in Proc. 44th IEEE Conf. on Decision and Control and European Control Conf., Sevilla, Spain, 2005, pp. 1361–1366.

[380]   D. Muñoz de la Peña, T. Alamo, and A. Bemporad, “A decomposition algorithm for feedback min-max model predictive control,” in Proc. 44th IEEE Conf. on Decision and Control and European Control Conf., Sevilla, Spain, 2005, pp. 5126–5131.

[381]   N. Giorgetti, G. Pappas, and A. Bemporad, “Bounded model checking of hybrid dynamical systems,” in Proc. 44th IEEE Conf. on Decision and Control and European Control Conf., Sevilla, Spain, 2005, pp. 672–677.

[382]   A. Bemporad, S. Di Cairano, and N. Giorgetti, “Model predictive control of hybrid systems with applications to supply chain management,” in Proc. 49th ANIPLA National Congress “Automazione 2005”, Napoli, Italy, Nov. 2005.

[383]   M. Lazar, W.P.M.H. Heemels, A. Bemporad, and S. Weiland, “On the stability and robustness of non-smooth nonlinear MPC,” in Proc. Int. Workshop on Assessment and Future Directions of NMPC, Freudenstadt-Lauterbad, Germany, Aug. 2005.

[384]   A. Bemporad, G. Bianchini, F. Brogi, and F. Barbagli, “Passivity analysis and passification of discrete-time hybrid systems,” in Proc. 16th IFAC World Congress, Prague, Czech Republic, 2005.

[385]   M. Lazar, W.P.M.H. Heemels, S. Weiland, and A. Bemporad, “On the stability of 2-norm based model predictive control of constrained PWA systems,” in Proc. American Contr. Conf., Portland, OR, 2005, pp. 575–580.

[386]   N. Giorgetti, A. Bemporad, H. E. Tseng, and D. Hrovat, “Hybrid model predictive control application towards optimal semi-active suspension,” in Proc. IEEE Int. Symp. on Industrial Electronics, Dubrovnik, Croatia, 2005, pp. 391–398.

[387]   N. Giorgetti, A. Bemporad, I.V. Kolmanovsky, and D. Hrovat, “Explicit hybrid optimal control of direct injection stratified charge engines,” in Proc. IEEE Int. Symp. on Industrial Electronics, Dubrovnik, Croatia, 2005, pp. 247–252.

[388]   M. Lazar, W.P.M.H. Heemels, S. Weiland, and A. Bemporad, “Stabilization conditions for model predictive control of constrained PWA systems,” in Proc. 43th IEEE Conf. on Decision and Control, Paradise Island, Bahamas, 2004, pp. 4595–4600.

[389]   J. Júlvez, A. Bemporad, L. Recalde, and M. Silva, “Event-driven optimal control of continuous Petri nets,” in Proc. 43th IEEE Conf. on Decision and Control, Paradise Island, Bahamas, 2004, pp. 69–74.

[390]   A. Bemporad, A. Garulli, S. Paoletti, and A. Vicino, “Data classification and parameter estimation for the identification of piecewise affine models,” in Proc. 43th IEEE Conf. on Decision and Control, Paradise Island, Bahamas, 2004, pp. 20–25.

[391]   D. Muñoz de la Peña, A. Bemporad, and C. Filippi, “Robust explicit MPC based on approximate multi-parametric convex programming,” in Proc. 43th IEEE Conf. on Decision and Control, Paradise Island, Bahamas, 2004, pp. 2491–2496.

[392]   D. Muñoz de la Peña, T. Alamo, A. Bemporad, and E. F. Camacho, “A dynamic programming approach for determining the explicit solution of MPC controllers,” in Proc. 43th IEEE Conf. on Decision and Control, Paradise Island, Bahamas, 2004, pp. 2479–2484.

[393]   A. Bemporad, N.L. Ricker, and J.G. Owen, “Model predictive control – New tools for design and evaluation,” in Proc. American Contr. Conf., Boston, MA, 2004, pp. 5622–5627.

[394]   M. Lazar, W.P.M.H. Heemels, S. Weiland, and A. Bemporad, “Stabilizing receding horizon control of piecewise linear systems: An LMI approach,” in 16^th Int. Symp. Mathematical Theory of Networks and Systems, Leuven, Belgium, 2004.

[395]   M.P. Silva, M. Ayala Botto, L. Pina, A. Bemporad, and J. Sá da Costa, “Robust optimal control of linear hybrid systems: An MLD approach,” in Sixth Portuguese Conference on Automatic Control (CONTROLO 2004), Faro, Portugal, 2004.

[396]   A. Bemporad, “Multiparametric nonlinear integer programming and explicit quantized optimal control,” in Proc. 42th IEEE Conf. on Decision and Control, Maui, Hawaii, USA, 2003, pp. 3167–3172.

[397]   A. Bemporad and N. Giorgetti, “Logic-based hybrid solvers for optimal control of hybrid systems,” in Proc. 42th IEEE Conf. on Decision and Control, Maui, Hawaii, USA, 2003, pp. 640–645.

[398]   A. Bemporad and C. Filippi, “Approximate multiparametric convex programming,” in Proc. 42th IEEE Conf. on Decision and Control, Maui, Hawaii, USA, 2003, pp. 3185–3190.

[399]   P. Tøndel, T. A. Johansen, and A. Bemporad, “Further results on multiparametric quadratic programming,” in Proc. 42th IEEE Conf. on Decision and Control, Maui, Hawaii, USA, 2003, pp. 3173–3178.

[400]   M.P. Silva, A. Bemporad, M.A. Botto, and J. Sá da Costa, “Optimal control of uncertain piecewise affine/mixed logical dynamical systems,” in European Control Conference, Sept. 2003.

[401]   F. Borrelli, M. Baotić, A. Bemporad, and M. Morari, “An efficient algorithm for computing the state feedback optimal control law for discrete time hybrid systems,” in Proc. American Contr. Conf., Denver, Colorado, 2003, vol. 6, pp. 4717–4722.

[402]   A. Bemporad, A. Garulli, S. Paoletti, and A. Vicino, “Set membership identification of piecewise affine models,” in 13th IFAC Symposium on System Identification, Rotterdam, The Netherlands, Aug. 2003.

[403]   A. Bemporad, D. Corona, A. Giua, and C. Seatzu, “Optimal state-feedback quadratic regulation of linear hybrid automata,” in IFAC Conf. on Analysis and Design of Hybrid Systems, Saint Malo, France, June 2003.

[404]   B. Picasso, S. Pancanti, A. Bemporad, and A. Bicchi, “Receding–horizon control of LTI systems with quantized inputs,” in IFAC Conf. on Analysis and Design of Hybrid Systems, Saint Malo, France, June 2003, pp. 259–264.

[405]   A. Bemporad, “An efficient technique for translating mixed logical dynamical systems into piecewise affine systems,” in Proc. 41th IEEE Conf. on Decision and Control, 2002, pp. 1970–1975.

[406]   A. Bemporad, A. Giua, and C. Seatzu, “A master-slave algorithm for the optimal control of continuous-time switched affine systems,” in Proc. 41th IEEE Conf. on Decision and Control, 2002, pp. 1976–1981.

[407]   A. Bemporad, A. Giua, and C. Seatzu, “Synthesis of state-feedback optimal controllers for switched linear systems,” in Proc. 41th IEEE Conf. on Decision and Control, 2002, pp. 3182–3187.

[408]   A. Bemporad, N. Giorgetti, I.V. Kolmanovsky, and D. Hrovat, “A hybrid system approach to modeling and optimal control of DISC engines,” in Proc. 41th IEEE Conf. on Decision and Control, 2002, pp. 1582–1587.

[409]   P. Tøndel, T. A. Johansen, and A. Bemporad, “Computation and approximation of piecewise affine control via binary search tree,” in Proc. 41th IEEE Conf. on Decision and Control, 2002, pp. 3144–3149.

[410]   A. Bemporad, N. Giorgetti, I.V. Kolmanovsky, and D. Hrovat, “Hybrid modeling and control of a direct injection stratified charge engine,” in Symposium on Advanced Automotive Technologies, ASME International Mechanical Engineering Congress and Exposition, New Orleans, LA, Nov. 2002.

[411]   A. Bemporad, A. Giua, and C. Seatzu, “An iterative algorithm for the optimal control of continuous–time switched linear systems,” in 6th Int. Work. on Discrete Event Systems (WODES), Zaragoza, Spain, Oct. 2002.

[412]   A. Bemporad, A. Teel, and L. Zaccarian, “L₂ anti-windup via receding horizon optimal control,” in Proc. American Contr. Conf., 2002.

[413]   B. Potočnik, A. Bemporad, F.D. Torrisi, G. Mušič, and B. Zupančič, “Scheduling of hybrid systems: Multi product batch plant,” in Proc. 15th IFAC World Congress, Barcelona, 2002.

[414]   B. De Schutter, W.P.M.H. Heemels, and A. Bemporad, “Max-plus-algebraic problems and the extended linear complementarity problem — algorithmic aspects,” in Proc. 15th IFAC World Congress, Barcelona, 2002.

[415]   A. Bemporad and C. Filippi, “Suboptimal explicit MPC via approximate multiparametric quadratic programming,” in Proc. 40th IEEE Conf. on Decision and Control, Orlando, Florida, 2001, pp. 4851–4856.

[416]   A. Bemporad, J. Roll, and L. Ljung, “Identification of hybrid systems via mixed-integer programming,” in Proc. 40th IEEE Conf. on Decision and Control, Orlando, Florida, 2001, pp. 786–792.

[417]   A. Bemporad, W.P.M.H. Heemels, and B. De Schutter, “On hybrid systems and closed-loop MPC systems,” in Proc. 40th IEEE Conf. on Decision and Control, Orlando, Florida, 2001, pp. 1645–1650.

[418]   W.P.H.M Heemels, B. de Schutter, and A. Bemporad, “On the equivalence of classes of hybrid dynamical models,” in Proc. 40th IEEE Conf. on Decision and Control, Orlando, Florida, 2001, pp. 364–369.

[419]   F.D. Torrisi and A. Bemporad, “Discrete-time hybrid modeling and verification,” in Proc. 40th IEEE Conf. on Decision and Control, Orlando, Florida, 2001, pp. 2899–2904.

[420]   P. Tøndel, T. A. Johansen, and A. Bemporad, “An algorithm for multi-parametric quadratic programming and explicit MPC solutions,” in Proc. 40th IEEE Conf. on Decision and Control, Orlando, Florida, 2001, pp. 1199–1204.

[421]   F. Borrelli, M. Baotić, A. Bemporad, and M. Morari, “Efficient on-line computation of constrained optimal control laws,” in Proc. 40th IEEE Conf. on Decision and Control, Orlando, Florida, 2001, pp. 1187–1192.

[422]   A. Bemporad, F. Borrelli, L. Glielmo, and F. Vasca, “Hybrid control of dry clutch engagement,” in Proc. European Control Conf., Porto, Portugal, Oct. 2001.

[423]   A. Bemporad, F. Borrelli, and M. Morari, “Piecewise linear robust model predictive control,” in Proc. European Control Conf., Porto, Portugal, Oct. 2001.

[424]   A. Bemporad and M. Morari, “Optimization-based hybrid control tools,” in Proc. American Contr. Conf., Arlington, VA, 2001.

[425]   A. Bemporad, F. Borrelli, L. Glielmo, and F. Vasca, “Optimal piecewise-linear control of dry clutch engagement,” in IFAC Workshop Advances in Automotive Control, Karlsruhe, Germany, Mar. 2001, pp. 33–38.

[426]   A. Bemporad, L. Giovanardi, and F.D. Torrisi, “Performance driven reachability analysis for optimal scheduling and control of hybrid systems,” in Proc. 39th IEEE Conf. on Decision and Control, Sydney, Australia, Dec. 2000, pp. 969–974.

[427]   A. Bemporad, F.D. Torrisi, and M. Morari, “Performance analysis of piecewise linear systems and model predictive control systems,” in Proc. 39th IEEE Conf. on Decision and Control, Sydney, Australia, Dec. 2000, pp. 4957–4962.

[428]   A. Bemporad, F. Borrelli, and M. Morari, “The explicit solution of constrained LP-based receding horizon control,” in Proc. 39th IEEE Conf. on Decision and Control, Sydney, Australia, Dec. 2000, pp. 632–637.

[429]   A. Bemporad, F. Borrelli, and M. Morari, “Optimal controllers for hybrid systems: Stability and piecewise linear explicit form,” in Proc. 39th IEEE Conf. on Decision and Control, Sydney, Australia, Dec. 2000, pp. 1810–1815.

[430]   A. Bemporad, K. Fukuda, and F.D. Torrisi, “On convexity recognition of the union of polyhedra,” in Proc. Int. Conf. on Advances in Convex Analysis and Global Optimization, Samos, Greece, June 2000, pp. 64–65.

[431]   A. Bemporad, L. Giovanardi, and F.D. Torrisi, “Robust simulation of nonlinear electronic circuits,” in Proceedings of the 8th IEEE International Workshop on Nonlinear Dynamics of Electronic Systems, R. Rovatti G. Setti and G. Mazzini, Eds., Catania, Italy, May 2000, pp. 131–135.

[432]   A. Bemporad, M. Morari, V. Dua, and E.N. Pistikopoulos, “The explicit linear quadratic regulator for constrained systems,” in Proc. American Contr. Conf., Chicago, IL, June 2000, pp. 872–876.

[433]   A. Bemporad, F. Borrelli, and M. Morari, “Piecewise linear optimal controllers for hybrid systems,” in Proc. American Contr. Conf., Chicago, IL, June 2000, pp. 1190–1194.

[434]   E.C. Kerrigan, A. Bemporad, D. Mignone, M. Morari, and J.M. Maciejowski, “Multi-objective prioritisation and reconfiguration for the control of constrained hybrid systems,” in Proc. American Contr. Conf., Chicago, IL, 2000, pp. 1694–1698.

[435]   A. Bemporad, N.A. Bozinis, V. Dua, M. Morari, and E.N. Pistikopoulos, “Model predictive control: A multi-parametric programming approach,” in Proc. European Symposium on Computer Aided Process Engineering-10, Florence, Italy, May 2000, pp. 301–306.

[436]   A. Bemporad, G. Ferrari-Trecate, and M. Morari, “Observability and controllability of piecewise affine and hybrid systems,” in Proc. 38th IEEE Conf. on Decision and Control, Phoenix, AZ, Dec. 1999, pp. 3966–3971.

[437]   A. Bemporad, G. Ferrari-Trecate, D. Mignone, M. Morari, and F.D. Torrisi, “Model predictive control — Ideas for the next generation,” in Proc. European Control Conf., Karlsruhe, Germany, Aug. 1999.

[438]   A. Bemporad, D. Mignone, and M. Morari, “Moving horizon estimation for hybrid systems and fault detection,” in Proc. American Contr. Conf., Chicago, IL, June 1999, pp. 2471–2475.

[439]   D. Mignone, A. Bemporad, and M. Morari, “A framework for control, fault detection, state estimation and verification of hybrid systems,” Proc. American Contr. Conf., pp. 134–138, June 1999.

[440]   A. Bemporad, D. Mignone, and M. Morari, “An efficient branch and bound algorithm for state estimation and control of hybrid systems,” in Proc. European Control Conf., Karlsruhe, Germany, Aug. 1999.

[441]   A. Bemporad, “Reducing conservativeness in predictive control of constrained systems with disturbances,” in Proc. 37th IEEE Conf. on Decision and Control, Tampa, FL, 1998, pp. 1384–1391.

[442]   A. Bemporad, “Predictive control of teleoperated constrained systems with unbounded communication delays,” in Proc. 37th IEEE Conf. on Decision and Control, Tampa, FL, 1998, pp. 2133–2138.

[443]   A. Bemporad and E. Mosca, “Constrained predictive control with terminal ellipsoid constraint and artificial Lyapunov functions,” in Proc. 36th IEEE Conf. on Decision and Control, San Diego, CA, 1997, pp. 3218–3219.

[444]   A. Bemporad, M. Di Marco, and A. Tesi, “Wall-following controllers for sonar-based mobile robots,” in Proc. 36th IEEE Conf. on Decision and Control, San Diego, CA, Dec. 1997, pp. 3063–3068.

[445]   A. Bemporad and A. Garulli, “Predictive control via set-membership state estimation for constrained linear systems with disturbances,” in Proc. European Control Conf., Bruxelles, Belgium, July 1997.

[446]   A. Bemporad, “Control of constrained nonlinear systems via reference management,” in Proc. American Contr. Conf., Albuquerque, NM, 1997, pp. 3343–3347.

[447]   A. Bemporad and T.J. Tarn, “On-line path parameterization for manipulators with input/state constraints,” in IEEE/ASME International Conference on Advanced Intelligent Mechatronics ’97, Tokio, June 1997, IEEE, New York.

[448]   A. Bemporad, A. Casavola, and E. Mosca, “Ottimizzazione in linea del set-point per processi industriali soggetti a saturazioni o vincoli sullo stato,” in Proc. 41th ANIPLA National Congress “Automazione 97”, Torino, Italy, Nov. 1997, In Italian.

[449]   A. Bemporad and E. Mosca, “Robust nonlinear reference filtering for constrained linear systems with uncertain impulse/step responses,” in Proc. 35th IEEE Conf. on Decision and Control, Kobe, Japan, Dec. 1996, pp. 3527–3528.

[450]   A. Bemporad, A. De Luca, and G. Oriolo, “Local incremental planning for a car-like robot navigating among obstacles,” in Proc. IEEE Conf. Robotics and Automation, Minneapolis, USA, Apr. 1996, pp. 1205–1211.

[451]   A. Bemporad, A. Casavola, and E. Mosca, “A nonlinear command governor for constrained control systems,” in Proc. 13th IFAC World Congress, San Francisco, CA, June 1996, pp. 473–478.

[452]   A. Bemporad, A. Casavola, and E. Mosca, “A predictive reference governor for constrained control systems,” in Proc. ASI - Annual ICIMS-NOE conference, Tolosa, France, June 1996, pp. 231–238.

[453]   A. Bellini, A. Bemporad, E. Franchi, N. Manaresi, R. Rovatti, and G. Torrini, “Analog fuzzy implementation of a vehicle traction sliding-mode control,” in Proc. ISATA 29th International Symposium on Automotive Technology and Automation, Florence, Italy, 1996, pp. 275–282.

[454]   A. Bemporad and E. Mosca, “Nonlinear predictive reference filtering for constrained tracking,” in Proc. European Control Conf., Roma, Italy, 1995, pp. 1720–1725.

[455]   A. Bemporad and E. Mosca, “Nonlinear predictive reference governor for constrained control systems,” in Proc. 34th IEEE Conf. on Decision and Control, New Orleans, LA, 1995, pp. 1205–1210.

[456]   A. Bemporad and E. Mosca, “Reference management predictive control,” in EURACO Workshop, Florence, Italy, Sept. 1995, pp. 463–490.

[457]   A. Bemporad and E. Mosca, “Constraint fulfilment in control systems via predictive reference management,” in Proc. 33rd IEEE Conf. on Decision and Control, Lake Buena Vista, FL, 1994, pp. 3016–3022.

[458]   A. Bemporad and E. Mosca, “Constraint fulfilment in feedback control via predictive reference management,” in Proc. 3rd IEEE Conf. on Control Applications, Glasgow, U.K., 1994, pp. 1909–1914.

CONFERENCE PAPERS (SUBMITTED)

[459]   A.D. Adeoye, P.C. Petersen, and A. Bemporad, “Regularized Gauss-Newton for optimizing overparameterized neural networks,” 2024, submitted for publication. Available on arXiv at http://arxiv.org/abs/2404.14875.

TOOLBOX MANUALS

[460]   A. Bemporad, M. Morari, and N.L. Ricker, Model Predictive Control Toolbox for MATLAB – User’s Guide, The Mathworks, Inc., 2004, http://www.mathworks.com/access/helpdesk/help/toolbox/mpc/.

[461]   A. Bemporad, Hybrid Toolbox – User’s Guide, Dec. 2003, http://cse.lab.imtlucca.it/~bemporad/hybrid/toolbox.

[462]   B. Stellato, G. Banjac, P. Goulart, A. Bemporad, and S. Boyd, “osQP - the operator splitting QP solver,” 2017.

[463]   G. Cimini, A. Bemporad, and D. Bernardini, “ODYS QP Solver,” ODYS S.r.l. ( https://odys.it/qp), Sept. 2017.

[464]   A. Bemporad, MLD2PWA.M: A MATLAB function for translating mixed logical dynamical systems into piecewise affine systems, University of Siena, 2002, See related web page at http://cse.lab.imtlucca.it/~bemporad/hybrid/tools/mld2pwa/.

[465]   F. Torrisi, A. Bemporad, G. Bertini, P. Hertach, D. Jost, and Mignone D., “Hysdel 2.0.5 - user manual,” Tech. Rep. AUT02-28, Automatic Control Laboratory, ETH Zurich, 2002.

[466]   A. Bemporad and D. Mignone, MIQP.M: A Matlab function for solving mixed integer quadratic programs, 2000, http://cse.lab.imtlucca.it/~bemporad/hybrid/tools/miqp.

[467]   A. Bemporad, M. Morari, and N.L. Ricker, “The MPC simulink library,” Tech. Rep. AUT01-08, Automatic Control Laboratory, ETH, Zurich, Switzerland, 2000.

MISCELLANEOUS

[468]   A. Agnetis and A. Bemporad, “Automazione,” in Enciclopedia della Scienza e della Tecnica “G. Treccani”, vol. 5. Rome, Italy, 2008, In Italian.

[469]   A. Bemporad, “Voci ‘attuatore’, ‘automatica’, ‘azionamento’, ‘controllo predittivo’, ‘domotica’, ‘retroazione’, ‘robot’, ‘servosistema’,” in Enciclopedia della Scienza e della Tecnica “G. Treccani”, vol. 6. Rome, Italy, 2008, In Italian.

TECHNICAL REPORTS

[470]   S.K. Mulagaleti, A. Bemporad, and M. Zanon, “A smoothening-based algorithm for the computation of input disturbance sets guaranteeing constrained output reachability,” 2022.

[471]   A.D. Adeoye and A. Bemporad, “SC-Reg: Training overparameterized neural networks under self-concordant regularization,” 2021, Available on arXiv at https://arxiv.org/abs/2112.07344.

[472]   A. Bemporad, “Piecewise linear regression and classification,” 2021, Available on arXiv at https://arxiv.org/abs/2103.06189. Code available at http://cse.lab.imtlucca.it/~bemporad/parc.

[473]   V.V. Naik and A. Bemporad, “Exact and heuristic methods for embedded mixed-integer quadratic programming based on accelerated dual gradient projection,” 2020, available on arXiv at https://arxiv.org/abs/2101.09264.

[474]   A. Bemporad, D. Bernardini, M. Livshiz, and B. Pattipati, “Supervisory model predictive control of a powertrain with a continuously variable transmission,” 2018.

[475]   C.A. Pascucci, S. Bennani, and A. Bemporad, “Real-time model predictive control for Mars powered descent with pin-point accuracy,” 2016.

[476]   G. Cimini, D. Bernardini, and A. Bemporad, “An efficient constraint selection strategy in dual active-set methods for model predictive control,” 2015.

[477]   M. Graf Plessen and A. Bemporad, “Subspace identification of linear time-invariant systems with missing data in the frequency or time domain based on nuclear-norm minimization,” 2015.

[478]   P. Patrinos, L. Stella, and A. Bemporad, “Forward-Backward truncated Newton methods for convex composite optimization,” 2014, http://arxiv-web3.library.cornell.edu/abs/1402.6655.

[479]   P. Sopasakis, A.K. Sampathirao, D. Barcelli, and A. Bemporad, “Centralized and decentralized hierarchical multi-rate control of constrained linear systems,” 2014, submitted for publication.

[480]   M. Graf Plessen and A. Bemporad, “A framework for learning to trade,” 2017.

[481]   M. Graf Plessen and A. Bemporad, “Recursive trajectory planning for autonomous vehicles using generalized elementary paths,” 2017.

[482]   A. Bemporad, D. Bernardini, and P. Patrinos, “A convex feasibility approach to anytime model predictive control,” Tech. Rep., IMT Institute for Advanced Studies, Lucca, Feb. 2015, http://arxiv.org/abs/1502.07974.

[483]   A. Bemporad, C.A. Pascucci, and C. Rocchi, “Hierarchical and model predictive control of a quadcopter unmanned aerial vehicle,” 2011.

[484]   A. Bemporad, F. Bianchi, and F. Rossi, “A wireless sensor measurement station for agricultural applications,” Tech. Rep. 2009-1, Dept. Information Engineering, University of Siena, Italy, 2009.

[485]   D. Muñoz de la Peña, T. Alamo, A. Bemporad, and E.F. Camacho, “Approximate feedback min-max model predictive control with recourse horizon,” 2007.

[486]   M. P. Silva, L. Pina, A. Bemporad, M. Ayala Botto, and J. Sá da Costa, “Robust optimal control of linear hybrid systems: An MLD approach,” 2004.

[487]   A. Bemporad, D. Muñoz de la Peña, and P. Piazzesi, “Optimal control of investments for quality of supply improvement in electrical energy distribution networks,” Tech. Rep. 2006-1, Dip. Ingegneria dell’Informazione, Univ. of Siena, 2006.

[488]   A. Bemporad and S. Di Cairano, “Modelling and optimal control of hybrid systems with event uncertainty,” Tech. Rep. 02/04, University of Siena, 2004, http://www.dii.unisi.it/~dicairano/papers/tr0204.pdf.

[489]   A. Bemporad, “Multiparametric nonlinear integer programming and explicit quantized optimal control,” Tech. Rep. 06/03, Dept. Information Engineering, University of Siena, Italy, 2003, http://cse.lab.imtlucca.it/~bemporad.

[490]   A. Bemporad, “Modeling, control, and reachability analysis of discrete-time hybrid systems,” Lecture Notes - DISC School on Hybrid Systems, Mar. 2003.

[491]   A. Bemporad and M. Egerstedt, “Discrete time minimum attention control,” 2002.

[492]   A. Bemporad and C. Filippi, “Suboptimal explicit RHC via approximate multiparametric quadratic programming,” Tech. Rep. AUT02-07, Automatic Control Laboratory, ETH Zurich, Switzerland, May 2002.

[493]   F. Rusconi, A. Bemporad, M. Morari, and R. Rovaglio, “Using MPC as master controller for integrated gasification combined cycle processes,” 2002.

[494]   A. Bemporad, L. Giovanardi, and F.D. Torrisi, “Performance driven reachability analysis for optimal scheduling and control of hybrid systems,” Tech. Rep. AUT00-15, Automatic Control Laboratory, ETH Zurich, Switzerland, Sept. 2000.

[495]   F.D. Torrisi, A. Bemporad, and D. Mignone, “HYSDEL - A language for describing hybrid systems,” Tech. Rep. AUT00-03, ETH Zurich, 2000, http://control.ethz.ch/~hybrid/hysdel.

[496]   A. Bemporad, J. Roll, and L. Ljung, “Identification of hybrid systems via mixed-integer programming,” Tech. Rep. AUT00-29, ETH, Zurich, Oct. 2000.

[497]   A. Bemporad, “Identification of hybrid systems: Global convergence via mixed-integer programming,” Tech. Rep. AUT00-28, ETH, Zurich, Sept. 2000.

[498]   C. Pedret, A. Poncet, K. Stadler, A. Toller, A. Glattfelder, A. Bemporad, and M. Morari, “Model-varying predictive control of a nonlinear system,” Tech. Rep. AUT00-07, ETH Zurich, Feb. 2000.

[499]   M. Anlauff, A. Bemporad, S. Chakraborty, D. Mignone P. Kutter, M. Morari, A. Pierantonio, and L. Thiele, “From ease in programming to easy maintenance : Extending DSL usability with Montages,” Tech. Rep., ETH Zurich, 1999.

[500]   V. Dua, E.N. Pistikopoulos, N. Bozinis, A. Bemporad, and M. Morari, “Multiparametric quadratic programming,” 1999.

[501]   A. Bemporad, A. De Luca, and G. Oriolo, “Hierachical local incremental planners for mobile robots navigating among obstacles,” Tech. Rep. 26/97, University of Florence, Dip. Sistemi e Informatica, 1997.

THESES

[502]   A. Bemporad, Reference Governors: On-Line Set-Point Optimization Techniques for Constraint Fulfillment, Ph.D. dissertation, Dipartimento di Sistemi e Informatica, University of Florence, Firenze, Italy, October 1997.

[503]   A. Bemporad, “Controllo predittivo in presenza di vincoli e gestione in linea del riferimento,” M.S. thesis, Università di Firenze, Facoltà di Ingegneria, Florence, Italy, Dec. 1993, In Italian.