Dynamic Identification for Robot Manipulators Based on Modified Fourier Series

Abstract

To deal with the problem of dynamic parameter identification of robot manipulators,a systematic identification procedure was proposed based on modified Fourier series.First,a static continuous friction model was involved to model joint friction for realizable friction compensation in controller design.Then,the robot dynamic model was expressed linearly with respect to dynamic parameter vector.Second,periodic modified Fourier series was designed as exciting trajectory,which satisfied velocity and acceleration boundary conditions.To minimize the sensitivity to measurement noise,the coefficients of modified Fourier series were optimized according to the condition number criterion using genetic algorithm.In addition,considering the measurement noise effects,maximum likelihood estimation method was adopted to obtain accurate parameter estimates.The proposed identification procedure had been implemented on the first three axes of 6-DOF robot manipulator.Experimental results show that the needed joint torques can be reconstructed accurately,and identification using modified Fourier series can achieve better accuracy than that using finite Fourier series.