Nonlinear Model Predictive Control: Stability and Design Steps

This lecture covers the principles of Nonlinear Model Predictive Control (NMPC), including stability analysis with and without terminal constraints, economic NMPC formulations, and the numerical implementation of NMPC. The instructor discusses the design steps for optimal control and NMPC, emphasizing the importance of stability, state estimation, and robustness considerations. Various concepts such as adjoints, multipliers, and the practical convergence of economic NMPC are explored. The lecture concludes with a summary of the key points and open research questions in the field.