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| Permanent magnet linear synchronous motor self-organizing probabilistic fuzzy neural network control |
| Zhang Zhen, Wang Limei |
| School of Electrical Engineering, Shenyang University of Technology, Shenyang 110870 |
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Abstract In this paper, a self-organizing probabilistic fuzzy neural network control method is used to improve the control performance of permanent magnet linear synchronous motor (PMLSM). Probabilistic fuzzy neural network (PFNN) can effectively to estimate of uncertainty factors in the system of, and compared with NN has strong robustness, but the structure is fixed, low membership degree of node control to the current system is poorer, difficult to adjust the system steady-state error in the process of dynamic, so this article on the basis of the adopted a self-organized probabilistic fuzzy neural network controller (SOPFNN). In the case of parameter learning, a structure learning algorithm is adopted to ensure that each node can play the maximum role in the control process and further improve the tracking performance of the system. Simulation results show that the self-organizing probabilistic fuzzy neural network control not only improves the position tracking performance of the system, but also improves the robustness of the system.
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Received: 13 April 2020
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| Cite this article: |
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Zhang Zhen,Wang Limei. Permanent magnet linear synchronous motor self-organizing probabilistic fuzzy neural network control[J]. Electrical Engineering, 2020, 21(12): 1-5.
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| URL: |
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http://dqjs.cesmedia.cn/EN/Y2020/V21/I12/1
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[1] TING C S, LIEU J F, LIU C S, et al.An adaptive FNN control design of PMLSM in stationary reference frame[J]. Journal of Control, Automation and Electrical Systems, 2016, 27(4): 391-405.
[2] 金鸿雁, 赵希梅. 永磁直线伺服系统递归小波Elman神经网络互补滑模控制[J]. 电机与控制学报, 2019, 23(10): 102-109.
[3] 赵希梅, 王晨光. 永磁直线同步电机的自适应增量滑模控制[J]. 电工技术学报, 2017, 32(11): 111-117.
[4] 彭振洲. 直线电机驱动的数控机床XY工作台轮廓误差控制系统设计[D]. 成都: 电子科技大学, 2013.
[5] 刘永恒. 高精度PMLSM迭代学习控制与实验研究[D]. 沈阳: 沈阳工业大学, 2013.
[6] CHEN S Y, LEE C Y, WU C H, et al.Intelligent motion control of voice coil motor using PID-based fuzzy neural network with optimized membership function[J]. Engineering Computations, 2016, 33(8): 2302-2319.
[7] LIN F T, HUANG Y S, TAN K H, et al.Intelligent- controlled doubly fed induction generator system using PFNN[J]. Neural Computing and Applications, 2013, 22(7/8): 1695-1712.
[8] LIN F J, LU K C, YANG B H.Recurrent fuzzy cerebellar model articulation neural network based power control of a single-stage three-phase grid- connected photovoltaic system during grid faults[J]. IEEE Transactions on Industrial Electronics, 2017, 64(2): 1258-1268.
[9] 熊渊琳, 方宝英. 基于TSK型递归模糊神经网络的永磁直线同步电机位置控制研究[J]. 机电工程, 2019, 36(4): 413-417.
[10] LIN Y Y, CHANG J Y, LIN C T.Identification and prediction of dynamic systems using an interactively recurrent self-evolving fuzzy neural network[J]. IEEE Transactions on Neural Networks and Learning Systems, 2013, 24(2): 310-321. |
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2020, Vol. 21 
