Fuzzy Adaptive Compliance Control Method for Charging Manipulator

作者：Jinhao Huang, S Chen, Wenxu Zheng, Pei–Yuan Su, Jinkun Li, Jixuan Zheng, Liang Yi, Hanzhen Xiao, Yi Peng, Zhifeng Huang · 年份：2023 · DOI：10.1109/icma57826.2023.10215768 · 被引用次数：2 · 研究领域：Robotic Path Planning Algorithms、Robot Manipulation and Learning、Industrial Automation and Control Systems

This paper presents an adaptive compliance control framework for the manipulator in electric vehicle charging tasks. The framework, based on impedance control, utilizes fuzzy rules to dynamically adjust impedance parameters for fast convergence to desired poses. The addition of an integral term reduces steady-state error. Experimental validation on the UR5 manipulator demonstrates the effectiveness of the method through comparative experiments. Compared to the static parameter compliance control method, the proposed method achieves a 20.4% reduction in convergence time and a 59.3% reduction in steady-state error for position tracking. For attitude tracking, the reductions are 56% and 95.1%, respectively. The proposed method achieves a steady-state error of 3.63mm for position and 0.036° for attitude. Charge port insertion and collision tests confirm the robot’s successful operation with the control algorithm, even in collision scenarios.