A fuzzy logic controller tuned with PSO for delta robot trajectory control

Abstract

In the view of the problem of tuning the parameters of the fuzzy logic controller (FLC) for Delta robot trajectory control, a method is put forward to tune the parameters of membership functions and the gains of the controller with particle swarm optimization (PSO). A PSO with dynamic parameters is proposed which makes the PSO has better performance in global search and faster convergence. The fitness function of the PSO was designed by using the time domain indices and integral of time-weighted-squared-error (ITSE) to optimize the performance of the controller. The simulation results show that FLC tuned by PSO has better performance and more robust than the PSO tuned PID controller for the DELTA robot trajectory control.