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Period-Doubling Bifurcation of Stochastic Fractional-Order Duffing System via Chebyshev Polynomial Approximation

机译:Chebyshev多项式近似随机分数达芙塞系统的时期加倍分叉

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摘要

Fractional-order calculus is more competent than integer-order one when modeling systems with properties of nonlocality and memory effect. And many real world problems related to uncertainties can be modeled with stochastic fractional-order systems with random parameters. Therefore, it is necessary to analyze the dynamical behaviors in those systems concerning both memory and uncertainties. The period-doubling bifurcation of stochastic fractional-order Duffing (SFOD for short) system with a bounded random parameter subject to harmonic excitation is studied in this paper. Firstly, Chebyshev polynomial approximation in conjunction with the predictor-corrector approach is used to numerically solve the SFOD system that can be reduced to the equivalent deterministic system. Then, the global and local analysis of period-doubling bifurcation are presented, respectively. It is shown that both the fractional-order and the intensity of the random parameter can be taken as bifurcation parameters, which are peculiar to the stochastic fractional-order system, comparing with the stochastic integer-order system or the deterministic fractional-order system. Moreover, the Chebyshev polynomial approximation is proved to be an effective approach for studying the period-doubling bifurcation of the SFOD system.
机译:在使用非光度和记忆效应的性质建模系统时,分数阶微积分比整数阶更能能力。与不确定性相关的许多现实世界问题可以用具有随机参数的随机分数级系统进行建模。因此,有必要分析关于内存和不确定性的那些系统中的动态行为。本文研究了具有受谐波激发的有界随机参数的随机分数级Duffing(SFOD的SFOD)系统的周期加倍分叉。首先,Chebyshev与预测校正器方法结合的多项式近似用于数值求解可以减少到等效确定性系统的SFOD系统。然后,分别呈现了全局和局部分析周期性分叉分叉。结果表明,随机参数的分数顺序和强度都可以作为分叉参数,其与随机分数阶系统特有的,与随机整数阶系统或确定性分数阶系统相比。此外,被证明是Chebyshev多项式近似是研究SFOD系统的周期性倍增分叉的有效方法。

著录项

  • 作者

    Youming Lei; Yanyan Wang;

  • 作者单位
  • 年度 2017
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  • 原文格式 PDF
  • 正文语种 eng
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