M12 – BERLIN 14/03/2016 ‐ 18/03/2016

Model Predictive Control

Jan M. Maciejowski
Cambridge University, Department of Engineering, UK

Abstract of the course

Model Predictive Control (MPC) is a model-based method which uses online optimization in real time to determine control signals. It is the only practical control method that takes account of system constraints explicitly, and the only ‘advanced control’ method to have been adopted widely in industry, particularly in petrochemicals and other process industries. There is intense interest in it for a variety of other applications, including automotive, aerospace, electric drives, smart grid and paper-making. This course covers the theory from basics through to current research concerns, as well as practical aspects. It includes paper-and-pencil and Matlab-based exercises. The course has been given in various universities since 2001, and has recently been comprehensively revised and updated.
The course is based on the textbook
Predictive Control with Constraints, by J.M. Maciejowski, Prentice-Hall, 2002.

Topics will include

• Various formulations of MPC
• Solution methods for MPC
• Stability and recursive feasibility
• Tuning MPC and reverse engineering
• Robust MPC
• Explicit MPC
• Nonlinear MPC
• ‘Economic’ MPC
• Case studies and applications