Mean-Square Stability and Stabilizability for LTI and Stochastic Systems Connected in Feedback
Abstract
In this paper, the feedback stabilization of a linear time-invariant (LTI) multiple-input multiple-output (MIMO) system cascaded by a linear stochastic system is studied in the mean-square sense. Here, the linear stochastic system can model a class of correlated stochastic uncertainties such as channel uncertainties induced by packet loss and random transmission delays in networked systems. By proposing a key parameter called coefficient of frequency variation to characterize the correlation of the stochastic uncertainties, we present a necessary and sufficient condition of the mean-square stability for this MIMO stochastic feedback system. After then a necessary and sufficient condition for the mean-square stabilizability is provided, which reveals a fundamental limit imposed by the system's unstable poles, nonminimum-phase (NMP) zeros, relative degrees (input delays), and the coefficient of frequency variation of the stochastic uncertainties. A numerical example is presented to illustrate the fundamental constraints in the mean-square stabilizability of MIMO networked systems with parallel communication channels.
Cite
@article{arxiv.2402.04074,
title = {Mean-Square Stability and Stabilizability for LTI and Stochastic Systems Connected in Feedback},
author = {Junhui Li and Jieying Lu and Weizhou Su},
journal= {arXiv preprint arXiv:2402.04074},
year = {2024}
}