Model Predictive Control (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.
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:
commercial MPC: convolution models, transfer functions, state-space models, and constraints;advanced topics: robust and stochastic MPC and MPC for nonlinear, hybrid, large-scale, and distributed systems; andapplications: a series of case studies in solar energy generation, hospital stock control, copper mining and aviation; along withexercises to help readers assess their progress, many with full or partial solutions in a solutions manual downloadable by adopting instructors.
MATLAB® programs to assist with the design aspects of the book and with reproducing some of the examples are included.
Model Predictive Control (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.
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:
commercial MPC: convolution models, transfer functions, state-space models, and constraints;advanced topics: robust and stochastic MPC and MPC for nonlinear, hybrid, large-scale, and distributed systems; andapplications: a series of case studies in solar energy generation, hospital stock control, copper mining and aviation; along withexercises to help readers assess their progress, many with full or partial solutions in a solutions manual downloadable by adopting instructors.
MATLAB® programs to assist with the design aspects of the book and with reproducing some of the examples are included.
Model Predictive Control (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.
From the reviews of the second edition:
"This text is an introduction to model predictive control, a control methodology which has encountered some success in industry, but which still presents many theoretical challenges. ... The book is of interest as an introduction to model predictive control, and a merit is the special presentation, connecting the subject intimately with industrial situations." (A. Akutowicz, Zentralblatt MATH, Vol. 1080, 2006)
"It is a much more ambitious work, seeking to inform practitioners how to implement MPC while at the same time serving as an advanced student text as well as reference for control researchers. ... The authors clearly see the text as a teaching aid since several chapters include exercises. ... In summary, a significant contribution to this important field for control academics, and some highly experienced MPC practitioners ... ." (Michael Brisk, www.tcetoday.com, February, 2008)
"This text is an introduction to model predictive control, a control methodology which has encountered some success in industry, but which still presents many theoretical challenges. ... The book is of interest as an introduction to model predictive control, and a merit is the special presentation, connecting the subject intimately with industrial situations." (A. Akutowicz, Zentralblatt MATH, Vol. 1080, 2006)
"It is a much more ambitious work, seeking to inform practitioners how to implement MPC while at the same time serving as an advanced student text as well as reference for control researchers. ... The authors clearly see the text as a teaching aid since several chapters include exercises. ... In summary, a significant contribution to this important field for control academics, and some highly experienced MPC practitioners ... ." (Michael Brisk, www.tcetoday.com, February, 2008)