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Predictive learning control for unknown nonaffine nonlinear systemstheory and applications /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Predictive learning control for unknown nonaffine nonlinear systemsby Qiongxia Yu ... [et al.].
Reminder of title:	theory and applications /
other author:	Yu, Qiongxia.
Published:	Singapore :Springer Nature Singapore :2023.
Description:	ix, 206 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Predictive control.
Online resource:	https://doi.org/10.1007/978-981-19-8857-8
ISBN:	9789811988578$q(electronic bk.)

Predictive learning control for unknown nonaffine nonlinear systemstheory and applications /
Predictive learning control for unknown nonaffine nonlinear systemstheory and applications /[electronic resource] :by Qiongxia Yu ... [et al.]. - Singapore :Springer Nature Singapore :2023. - ix, 206 p. :ill. (some col.), digital ;24 cm. - Intelligent control and learning systems,v. 82662-5466 ;. - Intelligent control and learning systems ;v. 3..

Chapter 1: Introduction -- Chapter 2 Predictive Learning Control for Unknown Systems -- Chapter 3 Constrained Predictive Learning Control -- Chapter 4 Predictive Learning Control for Systems with Varying Trial Lengths -- Chapter 5 Predictive Learning Control for Systems with Unknown Time Delay -- Chapter 6 Predictive Learning Control for Systems with Full Available States -- Chapter 7 Predictive Learning Control for Systems with Unavailable States -- Chapter 8 High-Speed Train Automatic Operation Systems -- Chapter 9 Fundamental Two-Region Urban Road Networks -- Chapter 10 Complex Large-Scale Multi-Region Urban Traffic Systems -- Chapter 11 Conclusions.

This book investigates both theory and various applications of predictive learning control (PLC) which is an advanced technology for complex nonlinear systems. To avoid the difficult modeling problem for complex nonlinear systems, this book begins with the design and theoretical analysis of PLC method without using mechanism model information of the system, and then a series of PLC methods is designed that can cope with system constraints, varying trial lengths, unknown time delay, and available and unavailable system states sequentially. Applications of the PLC on both railway and urban road transportation systems are also studied. The book is intended for researchers, engineers, and graduate students who are interested in predictive control, learning control, intelligent transportation systems and related fields.

ISBN: 9789811988578$q(electronic bk.)

Standard No.: 10.1007/978-981-19-8857-8doiSubjects--Topical Terms:

182316
Predictive control.

LC Class. No.: TJ217.6 / .Y8 2023

Dewey Class. No.: 629.8

Predictive learning control for unknown nonaffine nonlinear systemstheory and applications /
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245 0 0 $a Predictive learning control for unknown nonaffine nonlinear systems $h [electronic resource] : $b theory and applications / $c by Qiongxia Yu ... [et al.].
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490 1 $a Intelligent control and learning systems, $x 2662-5466 ; $v v. 8
505 0 $a Chapter 1: Introduction -- Chapter 2 Predictive Learning Control for Unknown Systems -- Chapter 3 Constrained Predictive Learning Control -- Chapter 4 Predictive Learning Control for Systems with Varying Trial Lengths -- Chapter 5 Predictive Learning Control for Systems with Unknown Time Delay -- Chapter 6 Predictive Learning Control for Systems with Full Available States -- Chapter 7 Predictive Learning Control for Systems with Unavailable States -- Chapter 8 High-Speed Train Automatic Operation Systems -- Chapter 9 Fundamental Two-Region Urban Road Networks -- Chapter 10 Complex Large-Scale Multi-Region Urban Traffic Systems -- Chapter 11 Conclusions.
520 $a This book investigates both theory and various applications of predictive learning control (PLC) which is an advanced technology for complex nonlinear systems. To avoid the difficult modeling problem for complex nonlinear systems, this book begins with the design and theoretical analysis of PLC method without using mechanism model information of the system, and then a series of PLC methods is designed that can cope with system constraints, varying trial lengths, unknown time delay, and available and unavailable system states sequentially. Applications of the PLC on both railway and urban road transportation systems are also studied. The book is intended for researchers, engineers, and graduate students who are interested in predictive control, learning control, intelligent transportation systems and related fields.
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