Fuzzy force control for industrial robots based on position inner loop

Xi'ao Yu; Hongjun Ma

doi:10.1117/12.3055361

12 December 2024 Fuzzy force control for industrial robots based on position inner loop

Xi'ao Yu, Hongjun Ma

Proceedings Volume 13439, Fourth International Conference on Testing Technology and Automation Engineering (TTAE 2024); 134390K (2024) https://doi.org/10.1117/12.3055361
Event: Fourth International Conference on Testing Technology and Automation Engineering (TTAE 2024), 2024, Xiamen, China

Abstract

Currently, industrial robots typically monitor and warn of environmental contact forces during press-fitting operations; however, their control modes are relatively simplistic, making it challenging to achieve compliant force processing. To enhance the press-fitting performance of industrial robots in manufacturing environments and to enable smoother force-controlled press-fitting, an innovative approach is proposed in this study. The method involves force tracking through an inner loop of position control, where the position is adjusted according to the magnitude of the force deviation using a fuzzy controller. This leads to higher accuracy in force tracking. The fuzzy controller is specifically designed to address the high stiffness and uncertainties inherent in the end-effector's contact environment, thereby enabling the industrial robot to exhibit strong adaptability. Experimental results demonstrate significant improvements in contact force tracking accuracy, along with excellent stability and robustness. This method facilitates soft and smooth press-fitting by industrial robots, thus improving both precision and efficiency. Furthermore, the adaptability of the robot system to the external working environment is enhanced, exhibiting superior disturbance rejection capabilities.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Xi'ao Yu and Hongjun Ma "Fuzzy force control for industrial robots based on position inner loop", Proc. SPIE 13439, Fourth International Conference on Testing Technology and Automation Engineering (TTAE 2024), 134390K (12 December 2024); https://doi.org/10.1117/12.3055361

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