Implementation and Comparison of Smart Controllers on dc-dc Buck-Boost Converter for DC Motor Drives Applications

Abstract

As a result of increasing power electronic applications in abundant fields, the use of these kinds of devices have been intensively arising in comparison with past decades. On the other hand, the use of intelligent controllers have permanently felt, especially in significant requests. This essay zeroed in on this controversial matter respecting the neural network and fuzzy logic controller schemes of a dc-dc Buck-Boost converter for DC motor drives application alike on variable DC voltages, and they are independently applied. The neural network learning algorithm is back propagation. By planning smart controller, the output voltage of dc-dc Buck-Boost converter and its performance during the process improved. In addition, for investigation the usefulness and effectiveness of the proposed controllers, some operations such as starting and reference voltage variations are verified. Simulation results show that the neural network controller has superior performance than fuzzy logic controller. In general, design of the system is executed by using MATLAB/Simulink.