- Enseignant: Guillaume Mercere
Méthodes de commande 2
This course offers a comprehensive introduction to Model Predictive Control (MPC), starting with an overview of its motivations and fundamental concepts. It begins with a brief review of linear least squares, setting the stage for the development of MPC techniques. The lecture then introduces the basic formulation of unconstrained model-based predictive control, assuming full state knowledge. Next, it covers state estimation using the discrete-time linear Kalman filter, and demonstrates how to integrate Kalman filtering with the basic MPC formulation. The course progresses to more advanced topics, including linear constrained model-based predictive control, and concludes with a discussion on linear constrained subspace-based predictive control.