Tutorial: model predictive control technology

This paper provides a brief tutorial on model predictive control (MPC) theory for linear and nonlinear models. The discussion of MPC with linear models covers the topics of steady-state target calculation, infinite horizon receding horizon regulation, resolving infeasibilities caused by constraints, and state estimation and disturbance models. The section on nonlinear models briefly discusses what is desirable from a theoretical perspective and what is possible from an implementation perspective and focuses on some current efforts to bridge this gap. The paper concludes with a brief outlook for future developments in the areas of nonlinear MPC, robustness, moving horizon state estimation and MPC of hybrid systems.