Abstract
Quantifying nonlinear dynamic behaviors, such as bifurcation and chaos, in nonlinear systems are currently being investigated. In this paper, permutation entropy is used to characterize these complex phenomena in nonlinear direct current-direct current (DC-DC) converter systems. A mode switching time sequence (MSTS), containing the information from different periodic states, is obtained in a DC-DC converter by reading the inductor current when altering the switching mode. To obtain the nonlinear characteristics of this system, the concept of permutation entropy of symbolic probability distribution properties is introduced and the structure of the chaotic system is reproduced based on the theory of phase space reconstruction. A variety of nonlinear dynamic features of the DC-DC converter are analyzed using the MSTS and permutation entropy. Finally, a current-mode-controlled buck converter is reviewed as a case to study the quantification of nonlinear phenomena using permutation entropy as one of the system parameters changes.
Highlights
Direct current-direct current (DC-DC) switching converters are a typical nonlinear system that enable the observation of nonlinear behaviors, such as period-doubling bifurcation, border collision bifurcation, frequency-locking phenomenon, quasi-period, and chaos [1,2,3,4,5]
(3) discontinuous conduction mode (DCM) and conduction mode (CCM) can be further divided into different patterns according todoes the different affect the value of the permutation entropy
Its basic idea is that the evolution of any component in the system the dynamic behavior of a system
Summary
Direct current-direct current (DC-DC) switching converters are a typical nonlinear system that enable the observation of nonlinear behaviors, such as period-doubling bifurcation, border collision bifurcation, frequency-locking phenomenon, quasi-period, and chaos [1,2,3,4,5]. The study of nonlinear behaviors is helpful for improving the performance of DC-DC converters
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