Impedance Sliding Mode Control With Adaptive Fuzzy Compensation for Robot-Environment Interacting
Heyu Hu, Xiaoqi Wang, Lerui Chen
IEEE Access · 2020
doi:10.1109/access.2020.2968954 (opens in a new tab)
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Abstract
In the field of robot research and application, improving the interaction performance between robots and the environment is the basic requirement of robot control. Hence, the position/force control problem needs to be solved. However, in practice, the model of the robot is usually inaccurate, and the working environment is usually uncertain. To solve the position/force control problem of the robot when the model and position are uncertain, a new method of impedance sliding mode control with adaptive fuzzy compensation (ISMCAF) is proposed. The dynamics of the robot are governed to follow a target impedance model and the interaction control objective is achieved. According to Lyapulov's theory, sliding mode control law and adaptive control law are designed to ensure the stability of the closed-loop system. The proposed method is further verified by simulation.
Abstract licence: CC BY-NC-ND
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