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Model predictive controlapproaches b...

Gao, Furong.

Model predictive controlapproaches based on the extended state space model and extended non-minimal state space model /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Model predictive controlby Ridong Zhang, Anke Xue, Furong Gao.
其他題名:	approaches based on the extended state space model and extended non-minimal state space model /
作者:	Zhang, Ridong.
其他作者:	Xue, Anke.
出版者:	Singapore :Springer Singapore :2019.
面頁冊數:	xv, 137 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer eBooks
標題:	Predictive control.
電子資源:	https://doi.org/10.1007/978-981-13-0083-7
ISBN:	9789811300837$q(electronic bk.)

Model predictive controlapproaches based on the extended state space model and extended non-minimal state space model /
Zhang, Ridong.

Model predictive controlapproaches based on the extended state space model and extended non-minimal state space model /[electronic resource] :by Ridong Zhang, Anke Xue, Furong Gao. - Singapore :Springer Singapore :2019. - xv, 137 p. :ill. (some col.), digital ;24 cm.

Introduction -- Model Predictive Control Based on Extended State Space Model -- Predictive Functional Control Based on Extended State Space Model -- Model Predictive Control Based on Extended Non-Minimal State Space Model -- Predictive Functional Control Based on Extended Non-minimal State Space Model -- Model Predictive Control Under Constraints -- PID Control Using Extended Non-minimal State Space Model Optimization -- Closed-loop System Performance Analysis -- Model Predictive Control Performance Optimized by Genetic Algorithm -- Industrial Application -- Further Ideas on MPC and PFC Using Relaxed Constrained Optimization.

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.

ISBN: 9789811300837$q(electronic bk.)

Standard No.: 10.1007/978-981-13-0083-7doiSubjects--Topical Terms:

182316
Predictive control.

LC Class. No.: TJ217.6 / .Z436 2019

Dewey Class. No.: 629.8

Model predictive controlapproaches based on the extended state space model and extended non-minimal state space model /
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520 $a 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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