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Model Predictive Control for AC Motors : Robustness and Accuracy Improvement Techniques / edited by Yaofei Han, Chao Gong, Jinqiu Gao

Contributor(s): Han, Yaofei, editor literario | Gong, Chao, editor literario | Gao, Jinqiu, editor literario
Material type: materialTypeLabelE-bookPublisher: Singapore : Springer International Publishing, 2022Edition: First edition 2022.Description: 1 recurso en línea (XI, 129 páginas) : 78 ilustraciones, 76 ilustraciones a color.ISBN: 9789811680663.Subject: Motores de corriente alternaOnline resources: Acceso a este recurso digital (usuarios Universidad Europea de Madrid)Digital Resources
Contents:
Model Predictive Control Principles For AC Motors -- Robustness against Stator Parameter Mismatch -- Robustness against Rotor Parameter Mismatch -- Accuracy Improvement of Model Predictive Control.
Summary: 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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Holdings
Item type Current library Collection Call number Status Date due Barcode Item holds
LIBRO-E NO PRÉSTAMO LIBRO-E NO PRÉSTAMO Madrid Digital Acceso Electrónico (UEM) Ciencias e Ingeniería TK2781 2022 EB (Browse shelf(Opens below)) Acceso electrónico eBook.18032087
Total holds: 0

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.

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