A Pragmatic Story of Model Predictive Control

Recent developments in model-predictive control promise remarkable opportunities for designing multi-input, multi-output control systems and improving the control of single-input, single-output systems. This volume provides a definitive survey of the latest model-predictive control methods available to engineers and scientists today.

Recent developments in model-predictive control promise remarkable opportunities for designing multi-input, multi-output control systems and improving the control of single-input, single-output systems. This volume provides a definitive survey of the latest model-predictive control methods available to engineers and scientists today.

Develop your knowledge of MPC controller design, maintenance, and troubleshooting.

by Basil Kouvaritakis (Author), Mark Cannon (Author)
Equips the student to deal with broad classes of system uncertainties with the first textbook treatment of stochastic predictive control
Gives the student an up-to-date source on robust predictive control including details of ten years’ of developments
Illustrates the tutorial material in each chapter with worked examples
Problems and solutions are provided for many of the chapters
Exposes students and practitioners to important new probabilistic applications of model predictive control

The book presents some recent specialized theoretical and practical works in the field of process control based on the model predictive control (MPC) method. It includes seven chapters that present studies on the application of MPC in various technical processes, such as the atmospheric plasma spray process, permanent magnet synchronous motors, monitoring of the pose of a walking person, monitoring of the heat treatment process of raw materials, discrete event processes, control of passenger vehicles, and natural gas sweetening processes.