DC MOTOR CONTROL USING GENETIC ALGORITHM BASED PID

This dissertation presents the research that had been done on the chosen topic, works
done and results acquired throughout the Final Year Project for two semesters, about
the DC Motor Control using Genetic Algorithm based PID. The objectives of this
project are to optimize speed control of the DC motor by using Genetic Algorithm
based PID, to improve the performances of the DC motor controller in term of rise
time, settling time, maximum overshoot and Integral of Time Absolute Error (ITAE)
and to decide the best parameters to be used for Genetic Algorithm that can optimize
the performance of a DC Motor ( eg: population size, mutation rate and crossover
value). First, the report discusses the types of DC motor available in industry
nowadays and the origination of Genetic Algorithm itself. Next, the paper sees the
implementation of DC motor control and the tuning available that has been
researched before. The usage of Genetic Algorithm is briefly explained which
comprises of three main phases; reproduction, crossover and mutation. For this
study, the software used is MATLAB/Simulink, where the implementation of the
chosen DC motor model is represented and Genetic Algorithm is incorporated into
the PID controller of the motor, to observe the performance of chosen parameters
available. Next, the paper shows the results of PID controller tuning and also the
results for the implementation of GA based PID controller. Comparison then is made
and discussed to see whether the results are as expected. Lastly, recommendation and
conclusion pertaining to the completion of this project are presented.