Genetic Based Fuzzy Logic Control Of SEDC Motor

This thesis primarily aims at offering an efficient technique of speed control for the small, independently excited SEDC motors utilised in a variety of applications, including industrial, commercial, and medical. The major objective of this work is to suggest a practical approach for controlling the speed of these weak motors. The natural optimization technique known as the genetic algorithm is employed in the suggested way to enhance the speed-controlled operation of the SEDC motor. The goal of this thesis work is to improve the values of several Performance parameters, such as rising time, time taken to settle, time taken to fall, peak overshoot, and steady state error, in order to regulate the motor in an efficient manner. The motor is operated using both the conventional PI controller and GA optimized controller MATLAB version R2013a was used to generate the SIMUINK MODEL for both controller operations. In terms of SEDC motor control, the proposed GA-optimized controller performs the best.