Predictive Control for Linear and Hybrid Systems - Borrelli, Francesco (University of California, Berkeley); Bemporad, Alberto; Morari, Manfred
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With a simple, unified approach, and with consideration of real-time applications, this book covers the theory of stability, feasibility, and robustness of model predictive control (MPC). It is for graduate and postgraduate students, as well as advanced control practitioners interested in the theory and/or implementation of predictive control.

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Produktbeschreibung
With a simple, unified approach, and with consideration of real-time applications, this book covers the theory of stability, feasibility, and robustness of model predictive control (MPC). It is for graduate and postgraduate students, as well as advanced control practitioners interested in the theory and/or implementation of predictive control.
Autorenporträt
Francesco Borrelli is a chaired Professor at the Department of Mechanical Engineering of the University of California, Berkeley. Since 2004 he has served as a consultant for major international corporations in the area of real-time predictive control. He was the founder and CTO of BrightBox Technologies Inc., and is the co-director of the Hyundai Center of Excellence in Integrated Vehicle Safety Systems and Control at the University of California, Berkeley. His research interests include constrained optimal control, model predictive control and its application to advanced automotive control, robotics and energy efficient building operation.