control course

Model Predictive Control

Teacher: Alberto Bemporad



Model Predictive Control (MPC) is a well-established technique for controlling multivariable systems subject to constraints on manipulated variables and outputs in an optimized way. Following a long history of success in the process industries, in recent years MPC is rapidly expanding in several other domains, such as in the automotive and aerospace industries, smart energy grids, and financial engineering.

The course is intended for students and engineers who want to learn the theory and practice of Model Predictive Control (MPC) of constrained linear, linear time-varying, nonlinear, stochastic, and hybrid dynamical systems, and numerical optimization methods for the implementation of MPC. The course will make use of the MPC Toolbox for MATLAB developed by the teacher and co-workers (distributed by The MathWorks, Inc.) for basic linear MPC, and of the Hybrid Toolbox for explicit and hybrid MPC.


General concepts of Model Predictive Control (MPC). MPC based on quadratic programming. General stability properties. MPC based on linear programming. Linear parameter-varying, time-varying, and nonlinear MPC. Models of hybrid systems: discrete hybrid automata, mixed logical dynamical systems, piecewise affine systems. MPC for hybrid systems based on on-line mixed-integer optimization. Multiparametric programming and explicit linear MPC, explicit solutions of hybrid MPC. Stochastic MPC: basic concepts, approaches based on scenario enumeration. Data-driven MPC. Selected applications of MPC in various domains, with practical demonstration of the MATLAB toolboxes.


Linear algebra and matrix computation, linear control systems, numerical optimization.

Monday April 12, 2021 11.00-13.00
Tuesday April 13, 2021 11.00-13.00
Wednesday April 14, 2021 11.00-13.00
Thursday April 15, 2021 11.00-13.00
Friday April 16, 2021 11.00-13.00
Monday April 17, 2021 11.00-13.00
Tuesday April 18, 2021 11.00-13.00
Wednesday April 19, 2021 11.00-13.00
Thursday April 20, 2021 11.00-13.00
Friday April 21, 2021 11.00-13.00

Virtual classroom.


Last update: April 8, 2021