Improving Control Stability for A Robot Arm Packaging System using Fuzzy Optimization

Abstract

This work addresses the issue of insufficient control stability in the robotic arm feeding system in the packaging production line by proposing an adaptive algorithm based on the fuzzy-optimized PID (Proportional-Integral-Derivative) controller. By establishing the D-H (Denavit-Hartenberg) kinematic model of the robotic arm and combining the MATLAB Robot Toolbox with the SIMULINK simulation platform, a fuzzy controller was designed with amplitude deviation and deviation rate as the inputs to dynamically adjust the PID parameters. Hardware integration was achieved based on the Mitsubishi FX2N series PLC (Programmable Logic Controller). Simulation results show that the adjustment time of the fuzzy PID control is 0.45s, which is reduced by 25% compared to the traditional PID (i.e., 0.6s), with the overshoot reduced from 6% to 0% and the steady-state error stabilized at 0mm. Through 10 sets of actual picking experiments, it was verified that the average time error under the fuzzy PID control is 0.37s with a standard deviation of 0.23s, which is a reduction of 55.4% and 85.6% compared to the traditional PID and direct start-up, respectively, which significantly improves the stability and efficiency of the robotic arm feeding system. This study proves that the fuzzy PID, through dynamic parameter optimization and disturbance compensation, can effectively address the control response delay and error accumulation of the robotic arm under non-ideal operating conditions, providing a high-precision and high-robustness solution for industrial packaging automation.