An optimized fuzzy logic controller for a parallel mechanism rehabilitation robot

Abstract

This paper focuses on the trajectory tracking control of the two-degree-of-freedom parallel manipulator. In order to have a robust tracking a fuzzy logic controller of which the boundary scales of the membership functions are optimized is developed. The performance of the developed optimized fuzzy logic controller is compared to the optimized proportional-integral-derivative controller. Particle swarm optimization algorithm is used with a fitness function, integral of time weighted absolute error (ITAE) performance index, during the optimization process. The performances of both controllers are measured using the ITAE performance index. In addition, other error-based objective functions called integral of squared error (ISE), integral of absolute error (IAE) and integral of time weighted squared error (ITSE) are calculated for a better comparison of the controllers. The results of the simulations show that the developed optimized fuzzy logic controller has better tracking performance compared to optimized proportional-integral-derivative controller.