Optimal Augmented Linear and Nonlinear PD Control Design for Parallel Robot Based on PSO Tuner

Abstract

This article presents the optimal control design for trajectory tracking of Delta\Par4-like parallel manipulator controlled by two augmented control schemes: Augmented PD Controller (APD) and Augmented Nonlinear PD (ANPD) Controller. Firstly, the Particle Swarm Optimization (PSO) technique is employed for optimal tuning of design parameters for each control structure in order to reach better dynamic performance. Then, two comparisons are made in order to evaluate the performance of parallel robot based on optimized ANPD and APD controllers. The first comparison is established in terms of tracking error accuracy due to the involved controllers, while the other one is based on the strength of robustness granted by each controller against variation of parallel robot parameters. The verification of performance comparisons is made via simulation within the environment of MATLAB/Simulink programming platform. The circular path is used for performance evaluation of controllers for trajectory tracking control. The simulated results have showed that ANPD controller outperforms the APD controller in terms of tracking accuracy and robustness.