Improved DBO algorithm tunes fuzzy-PD controller for robot manipulator trajectory tracking

This article proposes a novel approach for trajectory tracking of a six degrees-of-freedom (6-DOF) collaborative robot manipulator using an adaptive fuzzy proportional derivative (PD) controller. Based on the dynamic modeling of the robot manipulator, the PD control law is designed, and the improved dung beetle optimization (DBO) algorithm is introduced using the good point set (GPS) method for population initialization and the sine strategy for convergence factor adjustment. Furthermore, a fuzzy adaptive strategy is developed to adjust the PD controller gain based on real-time errors. This article uses discrete Lyapunov iterative stability to analyze the global asymptotic stability of the robot closed-loop system. The experimental results verify that the DBO-fuzzy-PD controller is superior to the original PD controller. The ISE value is reduced from 3.4140 to 0.0384, and the IAE value is reduced from 1.9876 to 0.1843. The DBO-fuzzy-PD controller has better tracking accuracy and response speed than traditional PD. Experimental results show that the proposed DBO-fuzzy-PD controller significantly enhances the trajectory tracking performance of the 6-DOF collaborative robot manipulator.

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