Decoupling control of bearingless permanent magnet-type synchronous motor using artificial neural networks-based inverse system method

International Journal of Modelling Identification and Control ◽

10.1504/ijmic.2009.029023 ◽

2009 ◽

Vol 8 (2) ◽

pp. 114 ◽

Author(s):

Xiao dong Sun ◽

Huang qiu Zhu ◽

Wei Pan

Keyword(s):

Neural Networks ◽

Artificial Neural Networks ◽

Permanent Magnet ◽

Synchronous Motor ◽

Inverse System ◽

Decoupling Control ◽

Inverse System Method ◽

System Method ◽

Artificial Neural

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Decoupling Control of Permanent Magnet Synchronous Motor With Support Vector Regression Inverse System Method

IEEE Access ◽

10.1109/access.2020.3039053 ◽

2020 ◽

Vol 8 ◽

pp. 212687-212698

Author(s):

Minghua Xie ◽

Lili Xie

Keyword(s):

Permanent Magnet ◽

Support Vector Regression ◽

Permanent Magnet Synchronous Motor ◽

Synchronous Motor ◽

Inverse System ◽

Decoupling Control ◽

Support Vector ◽

Inverse System Method ◽

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Decoupling control of 5 degree-of-freedom bearingless permanent magnet synchronous motor based on /spl alpha/-th order inverse system method

2005 International Conference on Electrical Machines and Systems ◽

10.1109/icems.2005.202534 ◽

2005 ◽

Author(s):

Decheng Fei ◽

Huangqiu Zhu ◽

Yukun Sun

Keyword(s):

Permanent Magnet ◽

Permanent Magnet Synchronous Motor ◽

Synchronous Motor ◽

Inverse System ◽

Degree Of Freedom ◽

Decoupling Control ◽

Inverse System Method ◽

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Nonlinear Decoupling Sliding Mode Control of Permanent Magnet Linear Synchronous Motor Based on α-th Order Inverse System Method

Procedia Engineering ◽

10.1016/j.proeng.2011.08.106 ◽

2011 ◽

Vol 15 ◽

pp. 561-567 ◽

Author(s):

Jing-Feng Mao ◽

Guo-Qing Wu ◽

Ai-Hua Wu ◽

Xu-Dong Zhang

Keyword(s):

Sliding Mode Control ◽

Permanent Magnet ◽

Sliding Mode ◽

Synchronous Motor ◽

Inverse System ◽

Inverse System Method ◽

Mode Control ◽

Linear Synchronous Motor ◽

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Decoupling control for five-phase fault-tolerant permanent-magnet motor by using SVM inverse system method

2014 International Joint Conference on Neural Networks (IJCNN) ◽

10.1109/ijcnn.2014.6889577 ◽

2014 ◽

Author(s):

Li Qu ◽

Guohai Liu ◽

Hao Zhang ◽

Yan Jiang

Keyword(s):

Permanent Magnet ◽

Fault Tolerant ◽

Inverse System ◽

Decoupling Control ◽

Permanent Magnet Motor ◽

Inverse System Method ◽

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Vector control of permanent magnet synchronous motor with surface magnet using artificial neural networks

2008 43rd International Universities Power Engineering Conference ◽

10.1109/upec.2008.4651647 ◽

2008 ◽

Author(s):

Jafar Zare

Keyword(s):

Neural Networks ◽

Artificial Neural Networks ◽

Vector Control ◽

Permanent Magnet ◽

Permanent Magnet Synchronous Motor ◽

Synchronous Motor ◽

Artificial Neural

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Internal Model Control for a Bearingless Permanent Magnet Synchronous Motor Based on Inverse System Method

IEEE Transactions on Energy Conversion ◽

10.1109/tec.2016.2591925 ◽

2016 ◽

Vol 31 (4) ◽

pp. 1539-1548 ◽

Author(s):

Xiaodong Sun ◽

Zhou Shi ◽

Long Chen ◽

Zebin Yang

Keyword(s):

Permanent Magnet ◽

Internal Model ◽

Permanent Magnet Synchronous Motor ◽

Synchronous Motor ◽

Internal Model Control ◽

Inverse System ◽

Inverse System Method ◽

System Method ◽

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The Decoupling Control of Induction Motor Based on Artificial Neural Network Inverse System Method

2010 International Conference on Electrical and Control Engineering ◽

10.1109/icece.2010.564 ◽

2010 ◽

Author(s):

Yongxian Song ◽

Juanli Ma ◽

Hanxia Zhang ◽

Naibao He

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Induction Motor ◽

Inverse System ◽

Decoupling Control ◽

Inverse System Method ◽

System Method ◽

Artificial Neural

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Decoupling control of bearingless synchronous reluctance motor based on inverse system method

2010 Chinese Control and Decision Conference ◽

10.1109/ccdc.2010.5498878 ◽

2010 ◽

Author(s):

Huangqiu Zhu ◽

Tingting Zhang ◽

Hualei Zou ◽

Xiaoyan Diao

Keyword(s):

Inverse System ◽

Decoupling Control ◽

Inverse System Method ◽

Synchronous Reluctance Motor ◽

System Method ◽

Reluctance Motor

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A Self-Learning Solution for Torque Ripple Reduction for Nonsinusoidal Permanent-Magnet Motor Drives Based on Artificial Neural Networks

IEEE Transactions on Industrial Electronics ◽

10.1109/tie.2013.2257136 ◽

2014 ◽

Vol 61 (2) ◽

pp. 655-666 ◽

Author(s):

Damien Flieller ◽

Ngac Ky Nguyen ◽

Patrice Wira ◽

Guy Sturtzer ◽

Djaffar Ould Abdeslam ◽

...

Keyword(s):

Neural Networks ◽

Artificial Neural Networks ◽

Permanent Magnet ◽

Torque Ripple ◽

Motor Drives ◽

Permanent Magnet Motor ◽

Torque Ripple Reduction ◽

Ripple Reduction ◽

Artificial Neural ◽

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The Inverse System Decoupling Control of the Permanent Magnet Synchronous Motor in D-q Synchronous Rotating Reference Frame

Procedia Engineering ◽

10.1016/j.proeng.2011.11.2605 ◽

2011 ◽

Vol 24 ◽

pp. 78-82 ◽

Author(s):

Xiaoning Li ◽

Yuan Wu ◽

Shijun Shen ◽

Xianfeng Zhao

Keyword(s):

Permanent Magnet ◽

Reference Frame ◽

Permanent Magnet Synchronous Motor ◽

Synchronous Motor ◽

Inverse System ◽

Decoupling Control ◽

Rotating Reference Frame

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