國立高雄大學圖資館 |

Language: English

Back

Model predictive controlapproaches b...

Gao, Furong.

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

Record Type:	Electronic resources : Monograph/item
Title/Author:	Model predictive controlby Ridong Zhang, Anke Xue, Furong Gao.
Reminder of title:	approaches based on the extended state space model and extended non-minimal state space model /
Author:	Zhang, Ridong.
other author:	Xue, Anke.
Published:	Singapore :Springer Singapore :2019.
Description:	xv, 137 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Predictive control.
Online resource:	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 /
LDR:02524nmm a2200325 a 4500 001 562943
003 DE-He213
005 20191230151351.0
006 m d
007 cr nn 008maaau
008 200227s2019 si s 0 eng d
020 $a 9789811300837$q(electronic bk.)
020 $a 9789811300820$q(paper)
024 7 $a 10.1007/978-981-13-0083-7 $2 doi
035 $a 978-981-13-0083-7
040 $a GP $c GP
041 0 $a eng
050 4 $a TJ217.6 $b .Z436 2019
072 7 $a TJFM $2 bicssc
072 7 $a TEC004000 $2 bisacsh
072 7 $a TJFM $2 thema
082 0 4 $a 629.8 $2 23
090 $a TJ217.6 $b .Z63 2019
100 1 $a Zhang, Ridong. $3 848262
245 1 0 $a Model predictive control $h [electronic resource] : $b approaches based on the extended state space model and extended non-minimal state space model / $c by Ridong Zhang, Anke Xue, Furong Gao.
260 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2019.
300 $a xv, 137 p. : $b ill. (some col.), digital ; $c 24 cm.
505 0 $a 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.
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.
650 0 $a Predictive control. $3 182316
650 1 4 $a Control and Systems Theory. $3 825946
650 2 4 $a Systems Theory, Control. $3 274654
650 2 4 $a Calculus of Variations and Optimal Control; Optimization. $3 274198
650 2 4 $a Energy Efficiency. $3 758284
700 1 $a Xue, Anke. $3 848263
700 1 $a Gao, Furong. $3 558636
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer eBooks
856 4 0 $u https://doi.org/10.1007/978-981-13-0083-7
950 $a Intelligent Technologies and Robotics (Springer-42732)