Stability Analysis of Large-Scale Distributed Networked Control Systems with Random Communication Delays: A Switched System Approach
arXiv:1503.03047 · doi:10.1016/j.sysconle.2015.08.011
Abstract
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.
References in corpus (1)
Cited by in corpus (6)
- A Decomposition Approach to Multi-Agent Systems with Bernoulli Packet Loss
- Mixed-gradients Distributed Filtered Reference Least Mean Square Algorithm -- A Robust Distributed Multichannel Active Noise Control Algorithm
- On the Convergence Analysis of Asynchronous Distributed Quadratic Programming via Dual Decomposition
- A Switched Dynamical System Framework for Analysis of Massively Parallel Asynchronous Numerical Algorithms
- A Stabilizing Control Algorithm for Asynchronous Parallel Quadratic Programming via Dual Decomposition
- Asynchronous Distributed Averaging: A Switched System Framework for Average Error Analysis