Model Predictive Control

Approaches Based on the Extended State Space Model and Extended Non-minimal State Space Model

Nonfiction, Science & Nature, Science, Other Sciences, System Theory, Technology, Automation
Cover of the book Model Predictive Control by Ridong Zhang, Anke Xue, Furong Gao, Springer Singapore
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Author: Ridong Zhang, Anke Xue, Furong Gao ISBN: 9789811300837
Publisher: Springer Singapore Publication: August 14, 2018
Imprint: Springer Language: English
Author: Ridong Zhang, Anke Xue, Furong Gao
ISBN: 9789811300837
Publisher: Springer Singapore
Publication: August 14, 2018
Imprint: Springer
Language: English

This monograph introduces the authors’ work on model predictive control system design using extended state space and extended non-minimal state space approaches. It systematically describes model predictive control design for chemical processes, including the basic control algorithms, the extension to predictive functional control, constrained control, closed-loop system analysis, model predictive control optimization-based PID control, genetic algorithm optimization-based model predictive control, and industrial applications. Providing important insights, useful methods and practical algorithms that can be used in chemical process control and optimization, it offers a valuable resource for researchers, scientists and engineers in the field of process system engineering and control engineering. 

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This monograph introduces the authors’ work on model predictive control system design using extended state space and extended non-minimal state space approaches. It systematically describes model predictive control design for chemical processes, including the basic control algorithms, the extension to predictive functional control, constrained control, closed-loop system analysis, model predictive control optimization-based PID control, genetic algorithm optimization-based model predictive control, and industrial applications. Providing important insights, useful methods and practical algorithms that can be used in chemical process control and optimization, it offers a valuable resource for researchers, scientists and engineers in the field of process system engineering and control engineering. 

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