Artificial Intelligence-Based Controller for DC-DC Flyback Converter

Abstract

This paper presents an intelligent voltage controller designed on the basis of an adaptive neuro-fuzzy inference system (ANFIS) for a flyback converter (FC) working in continuous conduction mode (CCM). The union of fuzzy logic (FL) and adaptive neural networks (ANN) makes ANFIS more robust against model parameters’ uncertainties and perturbations in input voltage or load current. ANFIS inherits the advantages of structured knowledge representation from FL and learning capability from NN. Comparative analysis showed that the ANFIS controller offers not only the superior transient response characteristics, but also excellent steady-state characteristics compared to those of the FL controller (FLC) and proportional–integral–derivative (PID) controllers, thus validating its superiority over these traditional controllers. For this purpose, MATLAB/Simulink environment-based simulation results are presented for validation of the proposed converter compensated system under all operating conditions.