Course abstract

Model Predictive Control (MPC) is one of the predominant advanced control techniques. MPC originated in the chemical process industry and is now applicable to a wide range of application areas. MPC is an optimization-based technique, which uses predictions from a model over a future control horizon to determine control inputs. This course will provide an overview of MPC, and will cover both theory and practical applications. The course will involve MATLAB-based hands-on learning modules for understanding and solving advanced control problems. The course will cover multiple aspects of MPC implementation, including dynamical system models, state estimation, unconstrained and constrained optimal control, and model identification.