Design and Development of Neural Fuzzy Controller for Boost Dc - Dc Converters

摘要

DC-DC converters are used to attain regulated DC output voltage even though there is variation in load resistance and DC input voltage. The application of DC-DC Boost converters are growing wide in the many areas (eg: HEV, domestic inverter etc). Conventionally, research papers are mainly concentrated on PID controllers in order regulate the output of Boost converter and suffered limitations such as severe system non-linearity, sensitivity to disturbances etc. The practical challenge in regulating the outcome of Boost converter necessitates the design of advanced control strategies to tackle the nonlinearity and stability. For this, it has been implemented in numerous control methods, which include: Fuzzy Logic Controller, Neural Network controller etc. An intelligent Adaptive TSK-type Neural Fuzzy Controller (ATNC), a fusion of both fuzzy logic and TSK- type neural network is designed in this paper for the control of DC-DC Boost converter. Simulation of the proposed ATNC scheme for Boost converter contributes superior output voltage regulation with slightest overshoot, settling time and smaller error parameters over conventional Fuzzy Logic Controller.