The main purpose of this course is to provide a compact and accessible overview of the essential elements of model predictive control (MPC), introducing deterministic and stochastic models, regulation, state estimation, dynamic programming (DP), tracking, disturbances, and some important performance properties such as closed-loop stability and zero offset to disturbances.
