Predictive Control for Linear and Hybrid Systems Borrelli Francesco University of California BerkeleyPaperback
Predictive Control for Linear and Hybrid Systems Borrelli Francesco University of California BerkeleyPaperback Model Predictive Control (MPC), the dominant advanced control approach in industry over…
Specifikacia Predictive Control for Linear and Hybrid Systems Borrelli Francesco University of California BerkeleyPaperback
Predictive Control for Linear and Hybrid Systems Borrelli Francesco University of California BerkeleyPaperback
Model Predictive Control (MPC), the dominant advanced control approach in industry over the past twenty-five years, is presented comprehensively in this unique book. 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. 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.
Drawing upon years of practical experience and using numerous examples and illustrative applications, the authors discuss the techniques required to design predictive control laws, including algorithms for polyhedral manipulations, mathematical and multiparametric programming and how to validate