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27 June 2022 Finite set predictive control study of permanent magnet synchronous motor
Jiaxin Liu, Huibo Liu
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Proceedings Volume 12253, International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2022); 122530I (2022) https://doi.org/10.1117/12.2639378
Event: Second International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2022), 2022, Qingdao, China
Abstract
Aiming at the problem of difficult allocation of the dq-axis current term weight coefficients of the cost function in the traditional finite control set model predictive current control of a permanent magnet synchronous motor, a finite control set model predictive current control method based on a neural network to optimize the cost function is proposed. In this paper, the neural network is constructed to assign the weights of the cost function by judging the changes of the speed deviation and the speed change rate, and the method improves the dynamic performance of the system and reduces the influence of the unreasonable assignment of the dqaxis weight coefficients on the system. The proposed method is verified by simulation analysis.
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Jiaxin Liu and Huibo Liu "Finite set predictive control study of permanent magnet synchronous motor", Proc. SPIE 12253, International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2022), 122530I (27 June 2022); https://doi.org/10.1117/12.2639378
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KEYWORDS
Neural networks
Control systems
Switching
Device simulation
Information technology
Neurons
Optimization (mathematics)
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