基于反步法的自适应神经网络EPS摩擦补偿*

doi:10.19562/j.chinasae.qcgc.2018.012.011

汽车工程 ›› 2018, Vol. 40 ›› Issue (12): 1454-1460.doi: 10.19562/j.chinasae.qcgc.2018.012.011

基于反步法的自适应神经网络EPS摩擦补偿^*

赵林峰¹, 邵文彬², 徐飞扬¹, 陈无畏¹

1.合肥工业大学汽车与交通工程学院,合肥 230009;
2.安徽江淮汽车集团股份有限公司技术中心,合肥 230601

收稿日期:2017-05-09 出版日期:2018-12-25 发布日期:2018-12-25
通讯作者: 赵林峰,副教授,E-mail:zhao.lin.feng@163.com
基金资助:
江苏省道路载运工具新技术应用重点实验室开放课题(BM20082061703)、国家自然科学基金(51675151,U1564201,61673154和51375131)资助。

EPS Friction Compensation with Adaptive Neural Network Based on Back-stepping Method

Zhao Linfeng¹, Shao Wenbin², Xu Feiyang¹, Chen Wuwei¹

1.School of Automotive and Transportation Engineering, Hefei University of Technology, Hefei 230009;
2.Technology Center, Anhui Jianghuai Automobile Co., Ltd., Hefei 230601

Received:2017-05-09 Online:2018-12-25 Published:2018-12-25

摘要/Abstract

摘要： 为消除EPS系统在制造和装配过程中造成的摩擦力矩个体差异的影响,本文中首先建立了EPS动力学模型,并考虑到转向系统摩擦的不确定性、非线性和个体差异,建立了基于LuGre模型的转向系统摩擦模型,设计了摩擦状态观测器。然后,提出了一种基于反步法的自适应神经网络控制策略,对EPS的摩擦进行补偿,并通过Lyapunov稳定定理证明其稳定性。最后,进行仿真和硬件在环试验,结果表明:采用自适应神经网络控制策略改善了电机电流跟踪性能,加入摩擦补偿后提高了EPS的转向轻便性和回正性能,且在一定程度上抑制了因摩擦不确定性和EPS产品个体差异性造成的摩擦力矩波动。

关键词: 电动助力转向, 摩擦补偿, LuGre模型, 反步法, 自适应神经网络

Abstract: In order to eliminate the effects of individual difference in friction torque of EPS system caused by manufacturing and assembling process, firstly an EPS dynamic model is established, and with consideration of the uncertainty, nonlinearity and individual difference of friction in steering system, a friction model for steering system is established based on LuGre model and a friction state observer is designed. Then an adaptive neural network control strategy based on back-stepping method is proposed to compensate the friction in EPS system, and its stability is proved by Lyapunov stability theorem. Finally, the results of simulation and hardware-in-the-loop test show that with adaptive neural network control strategy, motor current tracing performance is improved, and after friction compensation, the handiness and returnability of EPS are further enhanced and the fluctuation of friction torque, caused by the uncertainty of friction and the individual difference of EPS products is suppressed to certain extent

Key words: EPS, friction compensation, LuGre model, back-stepping, adaptive neural network

赵林峰, 邵文彬, 徐飞扬, 陈无畏. 基于反步法的自适应神经网络EPS摩擦补偿^*[J]. 汽车工程, 2018, 40(12): 1454-1460.

Zhao Linfeng, Shao Wenbin, Xu Feiyang, Chen Wuwei. EPS Friction Compensation with Adaptive Neural Network Based on Back-stepping Method[J]. , 2018, 40(12): 1454-1460.

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基于反步法的自适应神经网络EPS摩擦补偿^*

EPS Friction Compensation with Adaptive Neural Network Based on Back-stepping Method

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