一种改进的机器人动力学参数辨识方法  

Improved identification method of robot dynamic parameter

作　　者：张相胜 陈佳明 ZHANG Xiangsheng;CHEN Jiaming(Key Laboratory of Advanced Control of Light Industry Process,Ministry of Education,Jiangnan University,Wuxi,Jiangsu 214122,China)

机构地区：[1]江南大学轻工过程先进控制教育部重点实验室,江苏无锡214122

出　　处：《江苏大学学报（自然科学版）》2025年第1期50-56,共7页Journal of Jiangsu University：Natural Science Edition

基　　金：国家自然科学基金资助项目(61973139)。

摘　　要：针对六轴机器人动力学参数辨识中激励轨迹设计问题,提出了一种将改进差分进化(IDE)算法用于优化激励轨迹参数的方法.首先,用牛顿-欧拉(Newton-Euler)迭代法建立了六轴机器人动力学模型,将机器人最小惯性参数观测矩阵的条件数作为优化目标函数;其次,通过对差分进化算法的改进,引入反向最优最差策略改善种群初始值,采用自适应算法改进变异因子和交叉因子;最后,利用改进差分进化算法优化设计了满足机器人各个约束条件的傅里叶级数作为激励轨迹,进行机器人的参数辨识.试验结果表明,采用所提出的优化方法设计的激励轨迹可以充分激发机器人动力学特性,提高了机器人动力学参数辨识试验的抗噪声能力,为建立精确的机器人动力学模型提供参考.To solve the problem of excitation trajectory design in the six-axis robot dynamic parameter identification,the improved differential evolution(IDE)algorithm was proposed to optimize the excitation trajectory parameters.The dynamic model of the six-axis robot was established by Newton-Euler iteration method,and the condition number of the minimum inertia parameter observation matrix was taken as optimization objective function.By improving the differential evolution algorithm,the inverse optimal worst strategy was introduced to improve the initial value of the population,and the adaptive algorithm was used to improve the mutation factor and crossover factor.The improved differential evolution algorithm was used to optimize and design the Fourier series for meeting the constraints of robot and as excitation trajectory for identifying the parameters of robot.The experimental results show that the excitation trajectory designed by the proposed optimization method can give full play to the dynamic characteristics of robot and improve the anti noise ability of robot dynamic parameter identification experiment,which can provide foundation for establishing accurate robot dynamic model.

关 键 词：机器人 动力学模型 参数辨识 激励轨迹 改进差分进化算法 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置]