基于WLS-MBO算法的串联机器人动力学参数辨识  

Identification of dynamic parameters of tandem robot based on WLS-MBO algorithm

作　　者：张一楠 丁建完[1] ZHANG Yi-nan;DING Jian-wan(National CAD Support Software Engineering Research Center,Huazhong University of Science and Technology,Wuhan 430074,China)

机构地区：[1]华中科技大学国家CAD支撑软件工程技术研究中心,湖北武汉430074

出　　处：《计算机工程与科学》2023年第7期1274-1281,共8页Computer Engineering & Science

基　　金：国家重点研发计划(2019YFB1706501)。

摘　　要：针对六自由度串联机器人的参数辨识,提出了一种基于加权最小二乘和候鸟优化算法(WLS-MBO)的动力学参数辨识方法。首先基于串联机器人动力学原理,得到考虑了库伦粘滞摩擦参数的线性化动力学方程。采用五阶傅里叶级数作为辨识激励轨迹,通过机器人控制器驱动关节对激励轨迹进行跟踪,采集机器人运动过程中的关节位置和力矩数据,并通过加权最小二乘法(WLS)得到动力学参数的初始解。利用候鸟优化算法(MBO)对WLS的结果进行二次寻优,以提高动力学参数的辨识精度。实验结果表明:所提辨识方法具有较好的辨识效果,能够进一步提高辨识精度;MBO算法具有更优的全局搜索能力。Aiming at the parameter identification of six-degree-of-freedom tandem robots,a dynamic parameter iden-tification method based on weighted least squares and migrating birds optimization(WLS-MBO)is proposed.Firstly,based on the dynamic‘s principle of the robot,a linearized dynamic equation considering the Coulomb viscous friction parameters is obtained.The fifth-order Fourier series is used as the identification excitation trajectory,the robot controller drives the joints to track the excitation trajectory and collects the joint position and torque data during the robot movement,and the initial solution of the dynamic parameters is obtained by the weighted least square(WLS)method.Based on the results of the WLS method,the migrating birds optimization(MBO)is used for secondary optimization to improve the identification accuracy of parameters.The analysis of the results shows that the identification method has a good identification effect and can further improve the identification accuracy,and it verifies that the MBO has better global search ability.

关 键 词：串联机器人 参数辨识 候鸟优化算法 

分 类 号：TP242.2[自动化与计算机技术—检测技术与自动化装置]