Distributed Kalman Filtering in Presence of Unknown Outer Network Actuations

S. P. Talebi, S. Werner

    Research output: Contribution to journalArticleScientificpeer-review

    13 Citations (Scopus)
    228 Downloads (Pure)


    This letter presents a fully distributed approach for tracking state vector sequences over sensor networks in presence of unknown actuations. The problem arises in large-scale systems where modeling the full dynamics becomes impractical. In this letter, the network only considers a subsection of the overall system which it can detect while accounting other inputs as unknown actuations. First a centralized technique that can consolidate all the available observation information is introduced. Then, operations of this optimal centralized solution are decomposed in a manner to allow their implementation in a distributed fashion while allowing each agent to retain an estimate of both the state vector and unknown actuations. The filter is derived in both diffusion and consensus formulations. The diffusion formulation is intended as a cost-effective solution, while the consensus formulation trades implementation complexity for accuracy.
    Original languageEnglish
    Article number8454825
    Pages (from-to)186-191
    Number of pages6
    JournalIEEE Control Systems Letters
    Issue number1
    Publication statusPublished - 2019
    MoE publication typeA1 Journal article-refereed


    • Kalman filters
    • Complexity theory
    • Power grids
    • Observers
    • Monitoring
    • Electrical engineering
    • Kalman filtering
    • sensor networks
    • estimation
    • observers for linear systems


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