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Stability and stabilization of discrete-time linear compartmental switched systems via Markov chains.

Authors :
Li, Zhitao
Guo, Yuqian
Gui, Weihua
Source :
Automatica. Dec2024, Vol. 170, pN.PAG-N.PAG. 1p.
Publication Year :
2024

Abstract

The stabilizing switching signal design of discrete-time linear compartmental switched systems (DT-LCSSs) has been heretofore unsolved. It has been proven that a DT-LCSS is stabilizable if and only if it is stabilizable by a periodic switching signal. However, it still needs to be determined whether the period of a stabilizing switching signal can be confined within a bound. Moreover, the existing design method for stabilizing periodic switching signals requires the diagonal entries of system matrices of all subsystems to be strictly positive. In this study, we propose a novel approach to solve this problem completely. We construct a discrete-time Markov chain for a given DT-LCSS, termed the associated Markov chain, and prove the equivalence of stability and stabilizability between the DT-LCSS and the associated Markov chain. Based on this, verifiable necessary and sufficient conditions for stability and stabilizability are derived. Especially, the period of a stabilizing switching signal for an n -dimensional DT-LCSS can always be chosen within the bound n 2 − n + 1. We propose a state-independent stabilizing switching signal design method for general stabilizable DT-LCSSs. We also prove the equivalence between stabilizability by state-independent switching laws and stabilizability by state-dependent switching laws. A state-dependent global stabilizing switching signal design method is also proposed. Additionally, the proposed results are applied to the consensus analysis of discrete-time leader–follower multi-agent systems with switching communication digraphs. The effectiveness of the theoretical results is demonstrated by examples. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00051098
Volume :
170
Database :
Academic Search Index
Journal :
Automatica
Publication Type :
Academic Journal
Accession number :
179557713
Full Text :
https://doi.org/10.1016/j.automatica.2024.111850