Abstract
As the demand for individualized products increases, there is a need for advanced control at the supervisory level, where model predictive control (MPC) becomes an established solution in industry. This is an excellent text that provides numerous MPC algorithms supported by highly relevant, illustrative industry examples. The book opens with a comprehensive chapter about industry’s need for predictive control, reminding readers that MPC originated in business and expanded into academia, where it captured the attention of several seminal researchers. Addresses some of the following topics: major concepts of PID; properties of model-based control and requirements of MPCs; predictive function control (PFC); basic predictive control algorithms; principle components of dual-mode MPC; and constraint handling mechanisms. The book has a set of Matlab code (from MathWorks) and sources to help readers reproduce the illustrations in each chapter. A First Course in Predictive Control can be considered as a textbook, since it includes introductory subchapters to guide lecturers and help filter the sections for teaching from areas outside the course. In summary, this book provides an excellent course in MPC, presented in the form of a textbook, and great support for lecturers. It also offers a substantial starting point for MPC-related research for industrial applications.
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