
Considering that the variation of nonlinear characteristics of DC-DC converter with parameter k and the fact that entropy can reflect the statistical characteristic of numerical sequence, in this paper we propose a new method to estimate the nonlinear characteristics of DC-DC converter based on the information about entropy. In this study, taking one-order DCM Buck and Boost converter for example, the distributions of numerical sequences and entropies are analysed under different values of feedback gain k and initial values of x0. The results prove that the entropy of DC-DC converter is determined by feedback gain k and irrelevant to initial value x0, and its final value is smaller than the theoretical maximum value log2N (N is the number of partition), and that entropy can discriminate the period-doubling bifurcation and chaos. So a quantifiable nonlinear dynamical behavior index is obtained which can provide theoretical basis for understanding chaos characteristic and chaos control, and perfect the theoretical analysis method in DC-DC converters.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 4 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
