DC-DC变换器的符号时间序列描述及模块熵分析

本文提出了一种采用符号时间序列和熵理论分析DC-DC变换器非线性行为的方法.该方法首先用离散时间序列描述非线性连续系统,然后将其转换为由简单字符构成的符号序列,再用信息学方法计算出该符号序列的模块熵,从而得到一种新的可量化的非线性动力学行为统计指标.文中以一阶电压反馈DCM和二阶电流反馈CCM Boost变换器为例进行研究.研究结果表明,模块熵这种粗粒化的统计分析方法,能够量化DC-DC变换器的倍周期分岔和混沌行为,且能够准确地确定混沌行为的发生,是一种尚未在DC-DC变换器中提出的简单、实用的分析方法. 关键词： 符号时间序列 符号动力学 模块熵 Lyapunov指数

Symbolic time series characterization and block entropy analysis of DC-DC converters

A method based on symbolic time series and entropy theory is proposed to analyse the nonlinear behaviours of DC-DC converters. Firstly, the nonlinear continuous system is described by a discrete time series, which is then transferred to a symbol series composed of simple characters; and the series' block entropy is calculated by means of informatics methodology; consequently, a new quantifiable statistical index is obtained. This study takes a one-order voltage feedback DCM and a two-order current feedback CCM Boost converter as examples, and the results illustrate that the coarse-grained statistical method of block entropy, which can quantify the period-doubling and chaos behaviours in DC-DC converters and precisely confirm the appearance of chaos, is a simple and practical analysis method which has not been used in DC-DC converters yet.