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Distributed estimation algorithms on undirected chained graphs with explicit characterization of consensus
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DOI：10.1016/j.amc.2026.130208.png)
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Abstract
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• An original solution to a distributed identification problem on an undirected chain graph is presented. • A symmetrical neighbourhood-based decentralized parallel set of estimation algorithms (aiming at reducing the computational burden of a centralized estimation scheme) is designed and adopted. • The positive definite nature of a quadratic form associated with a tridiagonal block structure is crucial to proving consensus achievement, so that explicit characterization of persistency of excitation for the exponential convergence is innovatively provided, without resorting to typically used existence assertions. • Simulation results are given, with reference to real applications. • A general research line is followed, that is still capturing the interest of the research community, as demonstrated by several Elsevier AMC papers on related topics.
Keywords:
Parallel algorithm
Identifiability
Parameter estimation
Chained graph
Consensus
Linear time-varying system
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