A PSO-based automatic design of fuzzy inference system for speed control of DC motors

Special characteristics of the DC motors such as high reliability, flexibility, low consumption and simplicity of control have expanded the use of these motors in different industrials for instance steel plants, electric trains and etc. However, in the majority of applications, this system still controlled via traditional Proportional Integral Derivative (PID) controllers and in some cases, these controllers have been adjusted with intelligent methods. But this paper, in order to DC motor speed control, suggests a novel method to create a fuzzy logic inference system that is completely optimized through Particle Swarm Optimization (PSO) algorithm. The proposed approach has applied to a DC motor model in the MATLAB/Simulink software simulation environment and compared with different methods based on PID controllers. Simulation results show the suggested approach improved the various time response terms such as rise time, delay time and settling time for DC motor speed control.