Model Predictive Control by Camacho, Eduardo F.; Bordons, Carlos; Maestre, José M.;

Long description:

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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; and
• applications: a series of case studies in solar energy generation, hospital stock control, copper mining and aviation; along with
• exercises 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 third edition of ""Model Predictive Control"" provides a thorough introduction to theoretical and practical aspects of the most commonly used MPC strategies. It bridges the gap between the powerful but often abstract techniques of control researchers and the more empirical approach of practitioners. Its chapter structure has been completely overhauled to make the different ""flavours"" of MPC more easily findable and accessible. All of the material is thoroughly updated for the third edition with stochastic and distributed MPC making their debuts. New exercises, examples and case-studies have also been added throughout and MATLAB® programs simulating examples and assisting with design can be downloaded. This book gives the student access to a widely-used form of control which is required by many industrial careers.

Table of Contents:

Introduction to Model Predictive Control.- Part I: Commercial Model Predictive Control.- Model Predictive Control Using Convolution Models.- Model Predictive Control Using Transfer Functions.- Model Predictive Control Using State-Space Models.- Constrained Model Predictive Control.- Part II: Advanced Topics in Model Predictive Control.- Robust and Stochastic Model Predictive Control.- Model Predictive Control for Nonlinear and Hybrid Systems.- Model Predictive Control for Large-Scale and Distributed Systems.- New Trends in Model Predictive Control. Part III: Applications.- Applications.