Flatness-Based Decentralized Adaptive Backstepping Control of Cascaded DC–DC Boost Converters Using Legendre Polynomials

Abstract

In this paper, decentralized adaptive backstepping control of cascaded DC–DC boost converters is studied in the presence of load and voltage uncertainties and interactions between the converters. First, a cascaded boost converter average model that covers both continuous and discontinuous conduction modes is extracted. Afterward, flatness property is applied to transfer the cascaded system states into a semi-canonical form. Further, a novel decentralized backstepping controller is proposed to track the reference voltages. In this control strategy, Legendre polynomials are utilized to estimate the uncertainties and interactions adaptively. The control method is simple and robust with less computational burden due to the polynomial estimator’s application. Various simulations are performed for the cascaded DC–DC boost converters to indicate the effectiveness and performance of the proposed controller under the load and supply voltage changes.