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Distributed Kalman Filters With State Equality Constraints: Time-Based and Event-Triggered Communications
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
Rocket Force Univ Engn, Xian 710025, Peoples R China..
Chinese Acad Sci, Key Lab Syst & Control, Acad Math & Syst Sci, Beijing 100190, Peoples R China..
Hong Kong Univ Sci & Technol, Dept Elect & Comp Engn, Hong Kong, Peoples R China..
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2020 (English)In: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523, Vol. 65, no 1, p. 28-43Article in journal (Refereed) Published
Abstract [en]

In this paper, we investigate a distributed estimation problem for multiagent systems with state equality constraints (SEC). First, under a time-based consensus communication protocol, applying a modified projection operator and the covariance intersection fusion method, we propose a distributed Kalman filter with guaranteed consistency and satisfied SEC. Furthermore, we establish the relationship between consensus step, SEC, and estimation error covariance in dynamic and steady processes, respectively. Employing a space decomposition method, we show that the error covariance in the constraint set can be arbitrarily small by setting a sufficiently large consensus step. Besides, we propose an extended collective observability (ECO) condition based on SEC, which is milder than existing observability conditions. Under the ECO condition, through utilizing a technique of matrix approximation, we prove the boundedness of error covariance and the exponentially asymptotic unbiasedness of state estimate, respectively. Moreover, under the ECO condition for linear time-invariant systems with SEC, we provide a novel event-triggered communication protocol by employing the consistency, and give an offline design principle of triggering thresholds with guaranteed boundedness of error covariance. More importantly, we quantify and analyze the communication rate for the proposed event-triggered distributed Kalman filter, and provide optimization based methods to obtain the minimal (maximal) successive nontriggering (triggering) times. Two simulations are provided to demonstrate the developed theoretical results and the effectiveness of the filters.

Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC , 2020. Vol. 65, no 1, p. 28-43
Keywords [en]
Kalman filters, Observability, Covariance matrices, STEM, Protocols, State estimation, Collective observability, communication rate, consistency, distributed kalman filter, event-triggered, multiagent systems, state equality constraint (SEC)
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-267167DOI: 10.1109/TAC.2019.2906462ISI: 000506851100003Scopus ID: 2-s2.0-85077800929OAI: oai:DiVA.org:kth-267167DiVA, id: diva2:1391358
Note

QC 20200204

Available from: 2020-02-04 Created: 2020-02-04 Last updated: 2020-02-04Bibliographically approved

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