Perturbed Tumor Immunotherapy Domain of Attraction Estimation via the Arc-Length Function

Mojtaba Zarei, Kimia Javadi, A. Kalhor
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引用次数: 3

Abstract

This paper aims at the estimation of the Domain of Attraction (DoA) of the free tumor equilibrium point of perturbed tumor immunotherapy model via the Arc-Length Function (ALF). The ALFs are categorized among the maximal Lyapunov functions which are able to provide a more accurate estimation of the DoA in comparison to their other counterparts such as Rational Lyapunov Functions (RLFs), Sum Of Square (SOS) polynomial Lyapunov functions, and Optimal Quadratic Lyapunov Functions (OQLFs). There is no analytical method to construct the ALFs, however, some numerical methods have been proposed in the literature. Based on the existing method, one can approximate the ALF with a certain degree of a polynomial function. That the system under study has a polynomial structure was the main basis of the previously proposed method to estimate the DoA via the ALFs. However, the intended model in this paper describing the tumor-immune system competition dynamics contains non-polynomial terms. To cope with the aforementioned problem, the Taylor expansion of the non-polynomial terms are considered and by solving an optimization problem, one can calculate the corresponding lower boundary of the level set with the approximated ALF as an estimation of the DoA. In order to represent the performance of the employed method, the obtained result is compared with the reported result in the literature.
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通过弧长函数的吸引力估计的扰动肿瘤免疫治疗领域
本文旨在利用弧长函数(Arc-Length Function, ALF)估计扰动肿瘤免疫治疗模型游离肿瘤平衡点的吸引域(DoA)。alf被归类为最大Lyapunov函数,与其他对应函数(如有理Lyapunov函数(rlf),平方和(SOS)多项式Lyapunov函数和最优二次Lyapunov函数(OQLFs)相比,它们能够提供更准确的DoA估计。目前还没有解析的方法来构建alf,但文献中已经提出了一些数值方法。在现有方法的基础上,可以用一定程度的多项式函数逼近ALF。所研究的系统具有多项式结构,这是先前提出的利用alf估计DoA方法的主要依据。然而,本文拟建立的描述肿瘤-免疫系统竞争动力学的模型包含非多项式项。为了解决上述问题,考虑了非多项式项的泰勒展开式,通过求解优化问题,可以用近似的ALF作为DoA的估计来计算相应的水平集下边界。为了表示所采用方法的性能,将所得结果与文献报道的结果进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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