A Comparative Study of Fuzzy Logic Controller and Artificial Neural Network in Speed Control of Separately Excited DC Motor

This paper present a comparative study of speed control DC motor by using two different artificial intelligent controllers which are fuzzy logic controller (FLC) and artificial neural network (ANN). Intelligent controllers have gained wide popularity in the application of controlling system including DC motor speed control. The type of motor used in this project is separately excited DC motor. DC chopper is used to control the speed of DC motor by controlling their armature voltage of the motor. The switching of the DC chopper is control by using pulse width modulation (PWM) technique. This paper consists of two parts which are software development and hardware implementation. The software part is the development of the DC motor model with the controller to achieve the desired speed by using MATLAB/Simulink. In the hardware part, DC chopper is used to convert fixed DC voltage from power supply to variable DC voltage. IGBT is used to control the variable DC voltage and hence, achieve the target speed of the DC motor. DSPACE controller board is used for real-time interface of Simulink model and hardware development. In summary, this paper demonstrated the efficiency of both controllers designed for the DC motor in term of speed control in both simulation and hardware implementation.