Modeling and Performance of a Buck Converter Based on ‘Fuzzy Logic Soft Computing Technique’ for Low Voltage Operations

Abstract

This present paper details a ‘fuzzy logic soft computing technique’ of designing a controller for a buck converter operating at low voltages. The dc – dc buck converters find applications in solar energy technologies where they are used in solar control charging systems, battery charging systems, drones, in the automotive industry where there is integration of the engine and dc-dc motor drives resulting in hybrid electric drives or vehicle’s. Conventional controllers that is the proportional derivative control (pid) have dominated the control engineering field from the time of invention, however, these controllers present increased overshoot and a long time to achieve steady-state conditions. In this regard since fuzzy logic has intelligent capabilities, then a fuzzy logic soft computing-based controller is proposed in this paper. A mathematical analysis of the dc-dc buck design is also given and the modeling of the fuzzy logic control algorithms that avoids mathematical analysis is also discussed. Fuzzy control is one of the soft computing tools that consists of the observation made by people and their decision based on non-numerical information is also discussed. The performance analysis of the fuzzy controller is determined under constant load and variable decreasing voltage conditions. The analysis and simulation of the dynamic response in closed-loop frequency response are conducted in the Simulink platform in Matlab. The proposition of control is executed on a dc-dc step down converter for an input of 12V. This proposed fuzzy logic control technique provides a dc – dc buck converter system with increased overall operating efficiency and a very stable output.