基于改进细菌觅食算法的摩擦参数辨识方法

微特电机 ›› 2022, Vol. 50 ›› Issue (6): 31-35.

基于改进细菌觅食算法的摩擦参数辨识方法

周昊玥, 张建忠

东南大学电气工程学院,南京 210096

收稿日期:2022-04-09 发布日期:2022-07-08
作者简介:周昊玥(1998—),女,硕士研究生,主要从事电机控制相关工作。张建忠(1970—),男,博士,研究员,博士生导师,主要从事新能源发电和电力电子技术相关工作。

Parameter Identification of LuGre Friction Model Based on Improved Bacterial Foraging Optimization

ZHOU Haoyue, ZHANG Jianzhong

School of Electrical Engineering, Southeast University,Nanjing 210096,China

Received:2022-04-09 Published:2022-07-08

摘要/Abstract

摘要： 采用LuGre摩擦模型的前馈补偿可抑制非线性摩擦力的影响,提高伺服系统的低速性能。但LuGre摩擦模型高度非线性,动态参数难以准确获取,降低了摩擦补偿的效果。提出一种基于改进细菌觅食算法的LuGre摩擦模型参数辨识方法,引入自适应步长方法以提高动态参数的辨识精度和收敛速度。在MATLAB中实现了该算法,进行了参数辨识,证明该参数辨识方法能获得较高的辨识精度。在MATLAB/Simulink中搭建了伺服电机仿真模型,使用辨识结果进行了摩擦补偿效果验证,仿真结果证明了该方法的有效性。

关键词: 摩擦补偿, LuGre摩擦模型, 改进细菌觅食算法, 参数辨识

Abstract: The feedforward compensation using the LuGre friction model could suppress the influence of nonlinear friction and improved the low-speed performance of the servo system. However, the LuGre friction model was highly nonlinear, and the dynamic parameterswere difficult to obtain accurately, which reduced the effect of friction compensation. A LuGre friction model parameter identification method based on an improved bacterial foraging optimization was proposed, and an adaptive step size method was introduced to improve the identification accuracy and convergence speed of dynamic parameters. The proposed optimization was implemented in MATLAB, and parameter identification was carried out, whichproved that the proposed parameter identification method could obtain higher identification accuracy. A servo motor simulation model is built in MATLAB/Simulink, and the friction compensation effect was verified by using the identification results. The simulation results prove the effectiveness of the proposed method.

Key words: friction compensation, LuGre friction model, improved bacterial foraging optimization(IBFO), parameter identification

中图分类号:

TM351

周昊玥, 张建忠. 基于改进细菌觅食算法的摩擦参数辨识方法[J]. 微特电机, 2022, 50(6): 31-35.

ZHOU Haoyue, ZHANG Jianzhong. Parameter Identification of LuGre Friction Model Based on Improved Bacterial Foraging Optimization[J]. Small & Special Electrical Machines, 2022, 50(6): 31-35.

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