Stability Analysis of Distributed Estimators for Large-Scale Interconnected Systems: Time-Varying and Time-Invariant Cases

Fuente: arXiv
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Auteurs principaux: Hu, Zhongyao, Chen, Bo, Wang, Jianzheng, Ho, Daniel W. C., Zhang, Wen-An, Yu, Li
Format: Preprint
Publié: 2024
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author Hu, Zhongyao
Chen, Bo
Wang, Jianzheng
Ho, Daniel W. C.
Zhang, Wen-An
Yu, Li
author_facet Hu, Zhongyao
Chen, Bo
Wang, Jianzheng
Ho, Daniel W. C.
Zhang, Wen-An
Yu, Li
contents This paper studies a distributed estimation problem for time-varying/time-invariant large-scale interconnected systems (LISs). A fully distributed estimator is presented by recursively solving a distributed modified Riccati equation (DMRE) with decoupling variables. By partitioning the LIS based on the transition matrix's block structure, it turns out that the stability of the subsystem is independent of the global LIS if the decoupling variable is selected as the number of out-neighbors. Additionally, it is revealed that any LIS can be equivalently represented by a Markov system. Based on this insight, we show that the stability decoupling above can also be achieved if the decoupling variable equals the number of in-neighbors. Then, the distributed estimator is proved to be stable if the DMRE remains uniformly bounded. When the LIS is considered time-invariant, and by analyzing the spectral radius of a linear operator, it is proved that the DMRE is uniformly bounded if and only if a linear matrix inequality is feasible. Based on the boundedness result, we also show that the distributed estimator converges to a unique steady state for any initial condition. Finally, simulations verify the effectiveness of the proposed methods.
format Preprint
id arxiv_https___arxiv_org_abs_2411_06380
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Stability Analysis of Distributed Estimators for Large-Scale Interconnected Systems: Time-Varying and Time-Invariant Cases
Hu, Zhongyao
Chen, Bo
Wang, Jianzheng
Ho, Daniel W. C.
Zhang, Wen-An
Yu, Li
Systems and Control
93D99
I.6.6
This paper studies a distributed estimation problem for time-varying/time-invariant large-scale interconnected systems (LISs). A fully distributed estimator is presented by recursively solving a distributed modified Riccati equation (DMRE) with decoupling variables. By partitioning the LIS based on the transition matrix's block structure, it turns out that the stability of the subsystem is independent of the global LIS if the decoupling variable is selected as the number of out-neighbors. Additionally, it is revealed that any LIS can be equivalently represented by a Markov system. Based on this insight, we show that the stability decoupling above can also be achieved if the decoupling variable equals the number of in-neighbors. Then, the distributed estimator is proved to be stable if the DMRE remains uniformly bounded. When the LIS is considered time-invariant, and by analyzing the spectral radius of a linear operator, it is proved that the DMRE is uniformly bounded if and only if a linear matrix inequality is feasible. Based on the boundedness result, we also show that the distributed estimator converges to a unique steady state for any initial condition. Finally, simulations verify the effectiveness of the proposed methods.
title Stability Analysis of Distributed Estimators for Large-Scale Interconnected Systems: Time-Varying and Time-Invariant Cases
topic Systems and Control
93D99
I.6.6
url https://arxiv.org/abs/2411.06380