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arXiv 1503.03047eess.SYcs.SYmath.DS

大规模分布式网络化控制系统稳定性分析:基于切换系统的方法

Stability Analysis of Large-Scale Distributed Networked Control Systems with Random Communication Delays: A Switched System Approach

Texas A&M University(德克萨斯农工大学)

Kooktae Lee, Raktim Bhattacharya

AI总结:

本文研究了具有随机通信延迟的大规模分布式网络化控制系统的稳定性分析,提出了一种计算高效的简化模式模型,并考虑了马尔可夫跳变过程转移概率的不确定性,通过实例验证了方法的有效性。

摘要:

本文考虑了具有随机通信延迟的大规模分布式网络化控制系统的稳定性分析。稳定性分析在马尔可夫跳变线性系统框架下进行。尽管已有大量关于马尔可夫跳变系统稳定性分析的研究,但这些方法不适用于大规模系统,因为大量子系统导致切换模式数量极其庞大。为避免这一可扩展性问题,我们提出了一种新的简化模式模型用于稳定性分析,该模型计算高效。我们还考虑了马尔可夫跳变过程中转移概率包含不确定性的案例。我们提供了一种新的方法,用于估计不确定的马尔可夫转移概率矩阵的界限,以保证系统稳定性。所提出方法的效率和实用性通过实例得到验证。

英文摘要:

In this paper, we consider the stability analysis of large-scale distributed networked control systems with random communication delays between linearly interconnected subsystems. The stability analysis is performed in the Markov jump linear system framework. There have been considerable researches on stability analysis of Markov jump systems, however, these methods are not applicable to large-scale systems because large numbers of subsystems result in an extremely large number of the switching modes. To avoid this scalability issue, we propose a new reduced mode model for stability analysis, which is computationally efficient. We also consider the case in which the transition probabilities for the Markov jump process contain uncertainties. We provide a new method that estimates bounds for uncertain Markov transition probability matrix to guarantee the system stability. The efficiency and the usefulness of the proposed methods are verified through examples.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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