Dynamic parameter identification and nonlinear friction compensation method for safety perception of heavy explosion-proof robots. Issue 4 (2nd October 2022)

• Record Type: Journal Article
• Authors: Feng, Yanli; Zhang, Ke
• Is Part Of: Journal of control and decision. Volume 9:Issue 4(2022)
• Page Start: 455
• Page End: 464
• Publication Date: 2022-10-02
• Subjects: Heavy explosion-proof robots -- dynamic parameter identification -- nonlinear friction compensation; Control theory -- Periodicals; Decision making -- Periodicals; Robotics -- Periodicals; 003.505
• DOI: 10.1080/23307706.2021.2020693
• Languages: English
• ISSNs: 2330-7706

Abstract

ABSTRACT: This article focuses on the problem of how to accurately calculate the joint control torques when the explosion-proof robot performs collision detection without sensors and gives a complete solution. Nonlinear joint frictions are incorporated into the dynamic model of a robotic manipulator to improve calculation accuracy. A genetic algorithm is used to optimise the excitation trajectories to fully stimulate the robot dynamic characteristics. Effective and applicable data filtering and smoothing methods are proposed and the Iteratively Reweighted Least-Squares method based on the error term is applied to identify the robot dynamic parameters. Compared with Ordinary Least-Squares method, the proposed algorithm improves the accuracy of joint control torques estimation.