电工技术学报  2018, Vol. 33 Issue (10): 2392-2399    DOI: 10.19595/j.cnki.1000-6753.tces.171239
电机与电器 |
基于自适应修正拉盖尔递归神经网络的永磁直线同步电机反推控制
赵希梅, 吴勇慷
沈阳工业大学电气工程学院 沈阳 110870;
Backstepping Control Based on Adaptive Modified Laguerre ecurrent Neural Network for Permanent Magnet Linear Synchronous Motor
Zhao Ximei, Wu Yongkang
School of Electrical Engineering Shenyang University of Technology Shenyang 110870 China;
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摘要 针对永磁直线同步电机(PMLSM)伺服系统易受参数变化和非线性外部扰动等不确定性因素影响,提出了一种基于自适应修正拉盖尔递归神经网络(AMLRNN)的反推控制方法。首先,建立了含有不确定性的PMLSM动态模型。然后,采用AMLRNN估计系统中的不确定性,通过基于李雅普诺夫稳定性理论的在线参数训练方法推导出两个最优学习速率来加速参数收敛。该方法可避免传统的自适应反推控制系统中存在的“微分爆炸”问题及抖振现象,使系统具有良好的瞬态性能和鲁棒性能。最后,通过实验证明了所提出的控制方案是有效可行的,与传统的自适应反推控制系统相比,基于AMLRNN的反推控制系统的控制性能更加优越,明显减小了系统的位置跟踪误差。
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赵希梅
吴勇慷
关键词 永磁直线同步电机拉盖尔递归神经网络反推控制李雅普诺夫稳定性跟踪误差    
Abstract:A backstepping control approach based on adaptive modified Laguerre recurrent neural network (AMLRNN) was proposed for permanent magnet linear synchronous motor (PMLSM) servo system which is vulnerable to influence of the uncertainties, such as parameter variations and nonlinear external disturbances. Firstly, the dynamic model of PMLSM with the uncertainties was established. And then, two optimal learning rates were derived by the on-line parameter training methodology based on the Lyapunov stability theorem to accelerate parameter convergence. This method can avoid the inherent problem of explosion of complexity and chattering phenomenon existed in the general adaptive backstepping control system, and make the system have good transient performance and robust performance. Finally, the experimental results confirm that the proposed scheme is effective and feasible. Compared with the general adaptive backstepping control system, the backstepping control system using AMLRNN has more superior control performance, and the position tracking error of system is obviously reduced.
Key wordsPermanent magnet linear synchronous motor    Laguerre recurrent neural network    backstepping control    Lyapunov stability    tracking error   
收稿日期: 2017-08-29      出版日期: 2018-05-24
PACS: TP273  
基金资助:辽宁省自然科学基金计划重点项目(20170540677)和辽宁省教育厅科学技术研究项目(LQGD2017025)资助
通讯作者: 赵希梅 女,1979年生,副教授,博士生导师,研究方向为电机控制、机器人控制、智能控制等。E-mail: zhaoxm_sut@163.com   
作者简介: 吴勇慷 男,1992年生,硕士研究生,研究方向为电机控制、智能控制等。E-mail: wuyongkangch@gmail.com
引用本文:   
赵希梅, 吴勇慷. 基于自适应修正拉盖尔递归神经网络的永磁直线同步电机反推控制[J]. 电工技术学报, 2018, 33(10): 2392-2399. Zhao Ximei, Wu Yongkang. Backstepping Control Based on Adaptive Modified Laguerre ecurrent Neural Network for Permanent Magnet Linear Synchronous Motor. Transactions of China Electrotechnical Society, 2018, 33(10): 2392-2399.
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https://dgjsxb.ces-transaction.com/CN/10.19595/j.cnki.1000-6753.tces.171239          https://dgjsxb.ces-transaction.com/CN/Y2018/V33/I10/2392