A geometric approach for stability analysis of delay systems: Applications to network dynamics

Shijie Zhou, Wei Lin
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Abstract

Investigating the network stability or synchronization dynamics of multi-agent systems with time delays is of significant importance in numerous real-world applications. Such investigations often rely on solving the transcendental characteristic equations (TCEs) obtained from linearization of the considered systems around specific solutions. While stability results based on the TCEs with real-valued coefficients induced by symmetric networks in time-delayed models have been extensively explored in the literature, there remains a notable gap in stability analysis for the TCEs with complexvalued coefficients arising from asymmetric networked dynamics with time delays. To address this challenge comprehensively, we propose a rigorously geometric approach. By identifying and studying the stability crossing curves in the complex plane, we are able to determine the stability region of these systems. This approach is not only suitable for analyzing the stability of models with discrete time delays but also for models with various types of delays, including distributed time delays. Additionally, it can also handle random networks. We demonstrate the efficacy of this approach in designing delayed control strategies for car-following systems, mechanical systems, and deep brain stimulation modeling, where involved are complex-valued TCEs or/and different types of delays. All these therefore highlight the broad applicability of our approach across diverse domains.
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延迟系统稳定性分析的几何方法:网络动力学应用
研究具有时间延迟的多代理系统的网络稳定性或同步动力学在现实世界的众多应用中具有重要意义。此类研究通常依赖于求解所考虑系统围绕特定解线性化后得到的超越特征方程(TCE)。虽然文献中已经广泛探讨了对称网络延迟模型引起的实值系数 TCEs 的稳定性结果,但对于非对称网络时延动力学引起的复值系数 TCEs 的稳定性分析,仍存在明显差距。为了全面解决这一难题,我们提出了一种严格的几何方法。这种方法不仅适用于分析离散时间延迟模型的稳定性,也适用于包括分布式时间延迟在内的各种延迟模型。此外,它还能处理随机网络。我们在为汽车跟随系统、机械系统和深脑刺激建模设计延迟控制策略时证明了这种方法的有效性,其中涉及到复值 TCE 或/和不同类型的延迟。所有这些都凸显了我们的方法在不同领域的广泛适用性。
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