A Practical Auto-Tuning PID Control for Robot Manipulators Robust Against Significant Changes In Internal/External Dynamics

Abstract

This paper proposes a practical auto-tuning Proportional-Integral-Derivative (PID) control robust against significant internal and external dynamics changes for robot manipulators. The proposed PID control achieves robustness against significant internal and external dynamics with a modified Nussbaum class auto-tuning control method. The proposed PID control is practical as 1) there are only two tuning parameters, 2) each parameter has a clear meaning, and 3) the proposed PID control does not require a robot dynamics model. With the adoption of the forgetting factor, the proposed PID control prevents drift in the adaptive gain caused by the numerical integration of an update parameter accompanying sensor quantization error and noise. The experiment with a two degrees-of-freedom direct-drive robot verified the robustness of the proposed control against significant internal dynamics changes (4kg payload, 110% of robot arm mass) and external dynamics change due to stiff spring (180N/m spring). The constant PID tuned with the payload was unstable when there was no payload. These indicate that, under the significant robot and external dynamics changes, the proposed auto-tuning PID control is robust and can guarantee stability.