Speed Control of DC Motor Using Imperialist Competitive Algorithm Based on PI-Like FLC

This paper presents a method for optimizing PI like Fuzzy Logic Controller (FLC) using Imperialist Competitive Algorithm (ICA) and Genetic Algorithm (GA) in order to control the speed of DC motor. So as to achieve a better control performance, the ICA and GA optimize the parameters of FLC, which are Membership Functions (MFs) and gain factors. The number of rule in the designed Pi-like FLC is low and consequently requires less computation. This makes the FLC more suitable for real-time implementation, particularly at high-speed operating conditions. Simulation results show that optimizing the Pi-like FLC through ICA is the best performance compared to Pi-like FLC and GA optimized Pi-like FLC.