Computation of Bounds for Polynomial Dynamic Systems

Bounds for positive definite sets such as attractors of dynamic systems are typically characterized by Lyapunov-like functions. These Lyapunov functions and their time derivatives must satisfy certain definiteness conditions, whose verification usually requires considerable experience. If the system and a Lyapunov-like candidate function are polynomial, the definiteness conditions lead to Boolean combinations of polynomial equations and inequalities with quantifiers that can be formally solved using quantifier elimination. Unfortunately, the known algorithms for quantifier elimination require considerable computing power, meaning that many problems cannot be solved within a reasonable amount of time. In this context, it is particularly important to find a suitable mathematical formulation of the problem. This article develops a method that reduces the expected computational effort required for the necessary verification of definiteness conditions. The approach is illustrated using the example of the Chua system with cubic nonlinearity.

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Publication Details

Journal
Algorithms
Published
2025-12-12
DOI
https://doi.org/10.3390/a18120785
Primary Topic
Gene Regulatory Network Analysis
Type
article
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article

Computation of Bounds for Polynomial Dynamic Systems

Algorithms
Gene Regulatory Network Analysis
article

Computation of Bounds for Polynomial Dynamic Systems

article en

Abstract

Bounds for positive definite sets such as attractors of dynamic systems are typically characterized by Lyapunov-like functions. These Lyapunov functions and their time derivatives must satisfy certain definiteness conditions, whose verification usually requires considerable experience. If the system and a Lyapunov-like candidate function are polynomial, the definiteness conditions lead to Boolean combinations of polynomial equations and inequalities with quantifiers that can be formally solved using quantifier elimination. Unfortunately, the known algorithms for quantifier elimination require considerable computing power, meaning that many problems cannot be solved within a reasonable amount of time. In this context, it is particularly important to find a suitable mathematical formulation of the problem. This article develops a method that reduces the expected computational effort required for the necessary verification of definiteness conditions. The approach is illustrated using the example of the Chua system with cubic nonlinearity.

AlgorithmsVol. 18(12)
Technische Universität Dresden (DE)
Openalex Percentile: Top 38%
Gene Regulatory Network Analysis
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Computation of Bounds for Polynomial Dynamic Systems · Algorithms (2025) | TGRS Research Map | TGRS