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arXiv 2307.03030eess.SYcs.ROcs.SY
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基于遗传算法的非线性系统稳定性分析的李雅普诺夫函数搜索方法

Lyapunov function search method for analysis of nonlinear systems stability using genetic algorithm

A. M. Zenkin, A. A. Peregudin, A. A. Bobtsov

AI总结:

本文提出一种基于遗传算法搜索李雅普诺夫函数的新方法,将函数表示为状态向量非线性项加权幂次和,并用遗传算法确定未知系数,从而为具有可测状态向量的光滑连续非线性系统提供稳定性分析工具。

摘要:

本文考虑了一类广泛的具有可测状态向量的光滑连续动态非线性系统(控制对象)。问题在于寻找一个特殊函数(李雅普诺夫函数),该函数在李雅普诺夫第二方法的框架下保证上述非线性系统类的渐近稳定性。众所周知,李雅普诺夫函数的搜索是数学稳定性理论的“基石”。对于闭环线性定常系统以及具有显式线性动态和非线性静态部分的非线性对象,选择或寻找李雅普诺夫函数以分析稳定性的方法已经得到了充分研究(参见 Lurie、Yakubovich、Popov 等人的工作)。然而,对于更一般的非线性系统类,寻找李雅普诺夫函数的通用方法尚未被确定。目前存在大量针对非线性系统寻找李雅普诺夫函数的方法,但它们都在对控制对象结构施加的约束范围内运作。本文提出了另一种方法,该方法能够为自动控制理论领域的专家提供一种新的工具/机制,用于对具有可测状态向量的光滑连续动态非线性系统进行稳定性分析时的李雅普诺夫函数搜索。所提方法的本质在于将某个函数表示为非线性项之和,这些非线性项是对象状态向量的元素,乘以未知系数,并升到正的幂次。然后使用遗传算法选择未知系数,该算法应使该函数满足李雅普诺夫函数(在李雅普诺夫第二方法框架下)的所有必要条件。

英文摘要:

This paper considers a wide class of smooth continuous dynamic nonlinear systems (control objects) with a measurable vector of state. The problem is to find a special function (Lyapunov function), which in the framework of the second Lyapunov method guarantees asymptotic stability for the above described class of nonlinear systems. It is well known that the search for a Lyapunov function is the "cornerstone" of mathematical stability theory. Methods for selecting or finding the Lyapunov function to analyze the stability of closed linear stationary systems, as well as for nonlinear objects with explicit linear dynamic and nonlinear static parts, have been well studied (see works by Lurie, Yakubovich, Popov, and many others). However, universal approaches to the search for the Lyapunov function for a more general class of nonlinear systems have not yet been identified. There is a large variety of methods for finding the Lyapunov function for nonlinear systems, but they all operate within the constraints imposed on the structure of the control object. In this paper we propose another approach, which allows to give specialists in the field of automatic control theory a new tool/mechanism of Lyapunov function search for stability analysis of smooth continuous dynamic nonlinear systems with measurable state vector. The essence of proposed approach consists in representation of some function through sum of nonlinear terms, which are elements of object's state vector, multiplied by unknown coefficients, raised to positive degrees. Then the unknown coefficients are selected using genetic algorithm, which should provide the function with all necessary conditions for Lyapunov function (in the framework of the second Lyapunov method).

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