Stability Analysis of Nondifferentiable Systems

IF 2.6 2区 数学 Q1 MATHEMATICS, APPLIED
Jiwoon Sim, Tianxu Wang, Hao Wang
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引用次数: 0

Abstract

Differential equations with right-hand side functions that are not everywhere differentiable are referred to as nondifferentiable systems. This paper introduces three novel methods to address stability issues in nondifferentiable systems. The first method extends the linearization method as it fails when the equilibrium is in a nondifferentiable region. We find that the stability of a piecewise differentiable system aligns with the behavior of its subsystems as long as the “distance” between these subsystems is sufficiently small. The second method is to examine the eigenvalues of the symmetric part of the Jacobian matrix in the vicinity of the equilibrium. This method applies to functions with even weaker regularity conditions, and does not require the eigenvalues to have a negative upper bound (or positive lower bound) over the domain. The third method establishes a connection between nondifferentiable systems and their approximate counterparts, revealing that their stability can be consistent under certain conditions. Additionally, we reaffirm the first two results via the approximation method. Examples are provided to illustrate the applications of our main results, including piecewise differentiable systems, general nondifferentiable systems, and realistic scenarios.

Abstract Image

不可微系统的稳定性分析
具有非处处可微的右侧函数的微分方程被称为不可微系统。本文介绍了解决不可微系统稳定性问题的三种新方法。第一种方法是对线性化方法的扩展,因为线性化方法在平衡点处于不可微区域时失效。我们发现,只要子系统之间的“距离”足够小,一个分段可微系统的稳定性与子系统的行为一致。第二种方法是检查雅可比矩阵对称部分在平衡点附近的特征值。该方法适用于正则性条件更弱的函数,并且不要求特征值在定义域上具有负上界(或正下界)。第三种方法建立了不可微系统与其近似对应系统之间的联系,揭示了它们的稳定性在一定条件下是一致的。此外,我们通过近似方法重申了前两个结果。举例说明了我们的主要结果的应用,包括分段可微系统,一般不可微系统,和实际情况。
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来源期刊
Studies in Applied Mathematics
Studies in Applied Mathematics 数学-应用数学
CiteScore
4.30
自引率
3.70%
发文量
66
审稿时长
>12 weeks
期刊介绍: Studies in Applied Mathematics explores the interplay between mathematics and the applied disciplines. It publishes papers that advance the understanding of physical processes, or develop new mathematical techniques applicable to physical and real-world problems. Its main themes include (but are not limited to) nonlinear phenomena, mathematical modeling, integrable systems, asymptotic analysis, inverse problems, numerical analysis, dynamical systems, scientific computing and applications to areas such as fluid mechanics, mathematical biology, and optics.
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