Model Predictive Control: Classical, Robust, and Stochastic [Bookshelf

Abstract

Model predictive control (MPC) has become a dominant advanced control framework that has made a tremendous impact on both the academic and industrial control communities. Although the roots of MPC go back to the early 1960s, a remarkable surge in its popularity has taken place over the last two decades. Research in MPC has led to a plethora of advances addressing fundamental aspects, numerical considerations, and practical implementations. Particularly notable progress has been made in the fields of robust and stochastic MPC, which are now almost as well understood as their conventional MPC counterpart. Oxford’s contributions to MPC can be traced back to the early work of David W. Clarke on generalized predictive control. The Oxford control group, as well as theauthors of this book, have been very active in MPC and have developed a variety of specific approaches to MPC. This book offers a simplified and appealing overview of classical, robust, and stochastic MPC. These three areas are of paramount importance in MPC due to their fundamental nature and key role as the building blocks of more complex classical and contemporary MPC formulations. The book highlights a selection of works in which the authors of the book have contributed but also makes extensive use of methods originated and developed by other researchers in the area of control/MPC.