Paralleled DC–DC Converters Control Using Master–Slave Adaptive Fuzzy Backstepping Techniques

Abstract

Balanced current sharing and output voltage control of paralleled DC–DC converter modules are essential requirements for enhanced reliability and power capacity. These control goals are challenging due to the load, supply voltage, line impedance uncertainties, inter-couplings of the converters, and open circuit faults. To achieve these goals, this paper proposes two novel adaptive fuzzy backstepping control methods for two\xa0sets of paralleled DC–DC converters. The proposed controllers are exercised in a master–slave architecture. First, a master–slave adaptive fuzzy backstepping controller is suggested\xa0for a set of paralleled buck converters to deal with matched and mismatched uncertainties, and to ensure balanced current sharing. To counteract uncertainties, as well as interactions among the converters, adaptive fuzzy estimators are employed. However, the suggested control strategy is not applicable to the paralleled boost converters due to their non-minimum-phase nature. Therefore, a novel master–slave adaptive fuzzy backstepping controller with a conventional proportional-integral reference current generator is proposed to encompass paralleled boost converters. Moreover, a simple fault-tolerant structure is suggested\xa0to detect the open circuit faults and re-share the inductor currents. The stability of the proposed controllers is guaranteed through the Lyapunov stability theorem. The proposed adaptive fuzzy backstepping\xa0control strategies offer good output voltage quality and current sharing, despite the uncertainties, inter-couplings, and open circuit faults. Comparative simulations are carried out on sets of three paralleled buck and boost converters to demonstrate the effectiveness and performance of the new\xa0control methods.