東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Model predictive control for AC moto...

Han, Yaofei.

Linked to FindBook

Google Book

Amazon

博客來

Model predictive control for AC motors = robustness and accuracy improvement techniques /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Model predictive control for AC motors/ edited by Yaofei Han, Chao Gong, Jinqiu Gao.
Reminder of title:	robustness and accuracy improvement techniques /
other author:	Han, Yaofei.
Published:	Singapore :Springer Singapore : : 2022.,
Description:	xi, 129 p. :ill., digital ;24 cm.
[NT 15003449]:	Model Predictive Control Principles For AC Motors -- Robustness against Stator Parameter Mismatch -- Robustness against Rotor Parameter Mismatch -- Accuracy Improvement of Model Predictive Control.
Contained By:	Springer Nature eBook
Subject:	Predictive control. -
Online resource:	https://doi.org/10.1007/978-981-16-8066-3
ISBN:	9789811680663

Model predictive control for AC motors = robustness and accuracy improvement techniques /
Model predictive control for AC motorsrobustness and accuracy improvement techniques /[electronic resource] :edited by Yaofei Han, Chao Gong, Jinqiu Gao. - Singapore :Springer Singapore :2022. - xi, 129 p. :ill., digital ;24 cm.

Model Predictive Control Principles For AC Motors -- Robustness against Stator Parameter Mismatch -- Robustness against Rotor Parameter Mismatch -- Accuracy Improvement of Model Predictive Control.

This book introduces how to improve the accuracy and robustness of model predictive control. Firstly, the disturbance observation- and compensation-based method is developed. Secondly, direct parameter identification methods are developed. Thirdly, the seldom-focused-on issues such as sampling and delay problems are solved in this book. Overall, this book solves the problems in a systematic and innovative way. Chapter 2 is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

ISBN: 9789811680663

Standard No.: 10.1007/978-981-16-8066-3doiSubjects--Topical Terms:

667592
Predictive control.

LC Class. No.: TJ217.6 / .M63 2022

Dewey Class. No.: 629.8

Model predictive control for AC motors = robustness and accuracy improvement techniques /
LDR:01819nmm a2200337 a 4500 001 2298920
003 DE-He213
005 20220208110503.0
006 m d
007 cr nn 008maaau
008 230324s2022 si s 0 eng d
020 $a 9789811680663 $q (electronic bk.)
020 $a 9789811680656 $q (paper)
024 7 $a 10.1007/978-981-16-8066-3 $2 doi
035 $a 978-981-16-8066-3
040 $a GP $c GP
041 0 $a eng
050 4 $a TJ217.6 $b .M63 2022
072 7 $a TJFM $2 bicssc
072 7 $a GPFC $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 .M689 2022
245 0 0 $a Model predictive control for AC motors $h [electronic resource] : $b robustness and accuracy improvement techniques / $c edited by Yaofei Han, Chao Gong, Jinqiu Gao.
260 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2022.
300 $a xi, 129 p. : $b ill., digital ; $c 24 cm.
505 0 $a Model Predictive Control Principles For AC Motors -- Robustness against Stator Parameter Mismatch -- Robustness against Rotor Parameter Mismatch -- Accuracy Improvement of Model Predictive Control.
520 $a This book introduces how to improve the accuracy and robustness of model predictive control. Firstly, the disturbance observation- and compensation-based method is developed. Secondly, direct parameter identification methods are developed. Thirdly, the seldom-focused-on issues such as sampling and delay problems are solved in this book. Overall, this book solves the problems in a systematic and innovative way. Chapter 2 is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
650 0 $a Predictive control. $3 667592
650 0 $a Electric motors, Alternating current $x Control. $3 3595933
650 1 4 $a Control and Systems Theory. $3 3381515
650 2 4 $a Industrial Automation. $3 3591948
700 1 $a Han, Yaofei. $3 3595931
700 1 $a Gong, Chao. $3 3590329
700 1 $a Gao, Jinqiu. $3 3595932
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
856 4 0 $u https://doi.org/10.1007/978-981-16-8066-3
950 $a Intelligent Technologies and Robotics (SpringerNature-42732)