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Model predictive control for AC moto...

Han, Yaofei.

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

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Model predictive control for AC motors/ edited by Yaofei Han, Chao Gong, Jinqiu Gao.
其他題名:	robustness and accuracy improvement techniques /
其他作者:	Han, Yaofei.
出版者:	Singapore :Springer Singapore : : 2022.,
面頁冊數:	xi, 129 p. :ill., digital ;24 cm.
內容註:	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
標題:	Predictive control. -
電子資源:	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 /
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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.
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