Intelligent Speed Control of DC Servo Motor

Abstract

DC servomotors are conventionally controlled using P, PI, PD, and PID controllers. The controller design for such scheme requires exact mathematical model of the plant. On the other hand the controller is designed for only fixed loads. If load is changed, the controller has to be redesigned for other values of Kp, Ki and Kd constants of PID controller. In the presented work the comparative study of the controller designed with conventional PD controller, PD like fuzzy controller, Neural network controller and Neuro-fuzzy controller is done. The simulations are carried out in MATLAB SIMULINK. The improvements as expected form these state of art techniques is clearly seen form presented results. The overall design scheme using neuro-fuzzy controller is robust and results in improved dynamic and steady state response. The novelty of the presented research is that the fuzzy controller can cope up with the uncertainty and nonlinearity of the plant model and the neural network controller reduces the noise as well as imparts system robustness.