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Parameter Estimation for Robotic Manipulator Systems

Qianfeng Zhu, Zhihong Man, Zhenwei Cao, Jinchuan Zheng, Hai Wang

Year
2022
Citations
1
Access
Open access

Abstract

In this paper, a novel methodology for estimating the parameters of robotic manipulator systems is proposed. It can be seen that, for the purpose of parameter estimation, the input torque to each joint motor is designed as a linear combination of sinusoids. After the transient responses of joint angles exponentially converge to zero, the steady states of joint angle outputs can be extracted. Since the steady states of joint angles are the equivalent finite Fourier series, the coefficients of the steady state components of joint angles can be further extracted in a fundamental period. With the amazing finding that the steady states contain all dynamic information of manipulator systems, all unknown parameters of the system model can be accurately estimated with the extracted coefficients in finite frequency bands. The simulation results for a two-link manipulator are carried out to illustrate the effectiveness and robustness against measurement noise of the proposed method.

Keywords

Control theory (sociology)Robustness (evolution)Fourier seriesTorqueNoise (video)Joint (building)Estimation theoryRobot manipulatorSteady state (chemistry)Computer science

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