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基于OBL-SAMPSO算法的机器人零力控制摩擦力项辨识方法

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针对机器人零力控制中摩擦模型参数辨识,提出一种基于反向学习(OBL)策略的改进模拟退火(SA)寻优算法(OBL-SAMPSO算法)进行LuGre摩擦模型参数辨识.仿真结果表明:相较于传统的PSO算法,OBL-SAMPSO算法使参数辨识的绝对误差平均下降了85.86%;基于单关节实验平台进行LuGre摩擦辨识,并应用到其关节零力控制策略中,实现了具有良好柔顺性的拖曳操作.
Identification Method of Friction Force Parameter in Robot Force-free Control Based on OBL-SAMPSO Algorithm
An improved simulated annealing optimization algorithm(OBL-SAMPSO algorithm)based on reverse learning strategy is proposed for parameter identification of LuGre friction model in robot force-free control.The simulation results show that compared with the traditional PSO algorithm,the OBL-SAMPSO algorithm reduces the absolute error of parameter identification by 85.86%on average.LuGre friction identification is carried out based on the single joint experimental platform,and applied to the joint force-free control strategy.The towing operation with good compliance is realized.

OBL-SAMPSO algorithmforce-free controlLuGre friction modelparameter identification

王思源、张秋菊

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江南大学机械工程学院 无锡 214122

OBL-SAMPSO算法 零力控制 LuGre摩擦 参数辨识

2024

计算机与数字工程
中国船舶重工集团公司第七0九研究所

计算机与数字工程

CSTPCD
影响因子:0.355
ISSN:1672-9722
年,卷(期):2024.52(7)