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Comparison Between Artificial Bee Colony Algorithm, Shuffled Frog Leaping Algorithm and Nero-Fuzzy System in Design of Optimal PID Controllers

In this paper three optimum approaches to design PID controller for a Gryphon Robot are presented. The three applied approaches are Artificial Bee Colony, Shuffled Frog Leaping algorithms and nero-fuzzy system. The design goal is to minimize the integral absolute error and reduce transient response by minimizing overshoot, settling time and rise time of step response. An Objective function of these indexes is defined and minimized applying Shuffled Frog Leaping (SFL) algorithm, Artificial Bee Colony (ABC) algorithm and Nero-Fuzzy System (FNN). After optimization of the objective function, the optimal parameters for the PID controller are adjusted. Simulation results show that FNN has a remarkable effect on decreasing the amount of settling time and rise-time and eliminating of steady-state error while the SFL algorithm performs better on steady-state error and the ABC algorithm is better on decreasing of overshoot. In steady state manner, all of the methods react robustly to the disturbance, but FNN shows more stability in transient response.