Model Predictive Control for AC Motors : Robustness and Accuracy Improvement Techniques
Model Predictive Control for AC Motors : Robustness and Accuracy Improvement Techniques
edited by Yaofei Han, Chao Gong, Jinqiu Gao
- First edition 2022
- 1 recurso en línea (XI, 129 páginas) 78 ilustraciones, 76 ilustraciones a color
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.
9789811680663
10.1007/978-981-16-8066-3 doi
Motores de corriente alterna
TK2781 / 2022 EB
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.
9789811680663
10.1007/978-981-16-8066-3 doi
Motores de corriente alterna
TK2781 / 2022 EB