Design and comparative analysis of multiple controllers applied to DC-DC converters with large load range

Abstract

This paper presents a new controller design methodology for DC-DC converters operating with load varying in a large range. The proposed methodology employs a genetic algorithm to find LQR controllers with optimum performance by means of ITSE criterium and control action. A fuzzy logic based strategy is then employed to combine these local controllers, resulting in a strategy which guarantees good performance for a large range of load values. From Tellegen theorem, a load resistance estimator is obtained. The estimated resistance is used as the decision variable for the fuzzy supervisor controller. The proposed methodology is compared with the conventional LQR technique, based in a single controller, and with a controller switching strategy. Simulation results illustrate the superior performance of the converter with the application of the proposed methodology.