Extended State Observer Fuzzy-Approximation-Based Active Disturbances Rejection Control Method for Humanoid Robot with Trajectory Tracking

Abstract

This study aimed to propose an extended state observer fuzzy-approximation-based active disturbances rejection control (FAADRC) method for a dual-arm humanoid robotic system. The purpose of this control system was to provide disturbance estimation and compensation to enable the humanoid robots to track any continuous desired trajectory, even in the presence of environmental disturbances and parametric uncertainties. The proposed active disturbances rejection controller was analyzed using mathematical modeling, and the robot dual-arm motion information of a number of cases when they simulated the trajectory was examined to verify the model. The extended state observer adaptive fuzzy-approximation control strategy was designed combining the synthesis of the robust design, active disturbances rejection control, and Lyapunov function method so that the proposed FAADRC did not need to know the arms model of the humanoid robot precisely. In the control system proposed in this study, once the desired trajectories of the robot’s dual-arm positions were given, the FAADRC system was closed to any unknown functions and to the derivative of the virtual control law of the humanoid robot system. In this case, a robust controller based on an extended state observer was designed to realize the disturbance estimation and compensation. Using the proposed trajectory tracking, not only were the coordinate motions of a humanoid robot’s two arms generated, but the arms could also be controlled to move to the desired positions. The proposed closed-loop system under the FAADRC design was effective, and the asymptotic stability was successfully achieved. The numerical simulation showed the tracking error comparison and the estimated errors of the extended state observer. Two experimental tests were carried out to prove the performance of the algorithm presented in this study. The experimental results showed that the proposed FAADRC exhibited a better performance than the regular proportional integral derivative controller.