ISRAELI ASSOCIATION FOR AUTOMATIC CONTROL Workshop on Model Predictive Control for Constrained Linear and Hybrid Systems

Model Predictive Control (MPC) is currently the accepted standard in the process industries for handling complex constrained multivariable control problems. Here at each sampling time, starting at the current state, an open-loop optimal control problem is solved over a finite horizon. The optimal command signal is applied to the process only during the following sampling interval. At the next time step a new optimal control problem based on new measurements of the state of the system is solved over a shifted horizon. MPC popularity stems from the fact that the optimal solution relies on a dynamic model of the process, respects all input and output constraints, and minimizes a performance figure, which would be very hard to accomplish in any other way. Over the last 25 years MPC has become to dominate the process industry, where it has been employed for thousands of problems.