Model Predictive Control

<p><em>Model Predictive Control </em>(MPC), the classic textbook for students and practitioners seeking deep understanding of advanced control systems, is now revised, updated and reorganized in a streamlined third edition. The authors, renowned researchers in the field, cover an extensive range of topics that embraces the basic and the advanced, the theoretical and the applied.</p><p>The book offers advanced undergraduate and graduate students an accessible, step-by-step approach that enables them progressively to grasp and apply the concepts they are studying. For instructors, this is an invaluable curriculum resource packed with examples and case studies. The text features material on:</p><ul><li><span>commercial MPC: convolution models, transfer functions, state-space models, and constraints;</span></li><li><span>advanced topics: robust and stochastic MPC and MPC for nonlinear, hybrid, large-scale, and distributed systems; and</span></li><li><span>applications: a series of case studies in solar energy generation, hospital stock control, copper mining and aviation; along with</span></li><li><span>exercises to help readers assess their progress, many with full or partial solutions in a solutions manual downloadable by adopting <span>instructors</span>.</span></li></ul><p>MATLAB® programs to assist with the design aspects of the book and with reproducing some of the examples are included.</p><p><em>Model Predictive Control</em> (third edition)’s distinctive strength is its real-world relevance. It is an essential tool for future engineers; its focus on practical implementation, bridging the gap between academic theory and industrial practice and supplemented by exploration of optimization- and algorithm-related aspects of MPC, ensures a holistic treatment of the subject.</p>