Evaluation of a fuzzy-based sliding mode control strategy for a DC-DC buck converter

Abstract

DC-DC converters operate as semiconductor power devices in which transformers such as buck converters often cause nonlinear characteristics to the converter, while the output voltage of the converter affected by dynamic input voltage and load change. This paper presents a sliding mode control strategy using a fuzzy observer to provide a sustainable response and high performance for buck converters affected by uncertainties such as input voltage and resistance load. The control strategy includes two feedback loops in which an external control loop forces the output voltage to track the set voltage, and the output of the external control loop is adapted as a sliding surface to control the current through the inductor to track the set current, called the internal control loop. Design analysis, control law and Lyapunov stability of the control strategy are illustrated. The simulation is developed on the MATLAB-Simulink platform, the results are re-evaluated experimentally based on the self-built prototype of DC-DC buck converter. The simulated and experimental results have showed that the output voltage and current of the buck converter have tracked the set points from low to high values despite sudden changes in load as well as in input voltage in the presence of noise. The compatibility index normalized root mean square error of the measured voltage and current using the proposed algorithm is [96.34%±1.02%, 95.09%±3.04%] higher than that using the proportional integral (PI) algorithm which is [95.94% ± 3.01%, 85.72% ± 3.95%] in the presence of varying parameters.