Predictive Control for Linear and Hybrid Systems

Model predictive control (MPC), the dominant advanced control approach in industry over the past twenty-five years, is presented comprehensively in this unique book. With a simple, unified approach, and with attention to real-time implementation, it covers predictive control theory including the stability, feasibility, and robustness of MPC controllers. The theory of explicit MPC, where the nonlinear optimal feedback controller can be calculated efficiently, is presented in the context of linear systems with linear constraints, switched linear systems, and, more generally, linear hybrid systems. This book describes the techniques required to design predictive control laws, including algorithms for polyhedral manipulations, mathematical, and multi-parametric programming. Through many examples, the authors show how to validate the theoretical properties and to implement predictive control policies. Examples of the most important algorithms are featured in an accompanying free online MATLAB® toolbox, so that you can access sample solutions easily. Presents the main computational algorithms required to design predictive control algorithms Includes examples throughout to illustrate how to use the proposed algorithms and computational tools in order to transfer theory into practice Uses simple formalism to break down the main principles of model predictive control (MPC) for students struggling to understand the complex theory

• ISBN: 9781107652873
• Editorial: CAMBRIDGE UNIVERSITY PRESS
• Encuadernacion: Rústica
• Páginas: 440
• Fecha Publicación: 01/04/2017
• Nº Volúmenes: 1
• Idioma: