Journal
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
Volume 65, Issue 4, Pages 1792-1799Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TAC.2019.2934389
Keywords
Ellipsoids; Signal processing algorithms; Nonlinear systems; Estimation; Kalman filters; Time-varying systems; Sensors; Discrete-time nonlinear systems; distributed filtering; event-triggered protocols; sensor networks; set-membership filtering (SMF)
Funding
- National Natural Science Foundation of China [61573246, 61873148]
- Australian Research Council Discovery Project [DP160103567]
- Natural Science Foundation of Shanghai [18ZR1427000]
- Alexander von Humboldt Foundation of Germany
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This paper is concerned with the distributed set-membership filtering problem for a class of general discrete-time nonlinear systems under event-triggered communication protocols over sensor networks. To mitigate the communication burden, each intelligent sensing node broadcasts its measurement to the neighboring nodes only when a predetermined event-based media-access condition is satisfied. According to the interval mathematics theory, a recursive distributed set-membership scheme is designed to obtain an ellipsoid set containing the target states of interest via adequately fusing the measurements from neighboring nodes, where both the accurate estimate on Lagrange remainder and the event-based media-access condition are skillfully utilized to improve the filter performance. Furthermore, such a scheme is only dependent on neighbor information and local adjacency weights, thereby fulfilling the scalability requirement of sensor networks. In addition, an optimization algorithm is developed to minimize the trace of the estimated ellipsoid set, and the effect from the adopted event-triggered threshold is thoroughly discussed as well. Finally, a simulation example is utilized to illustrate the usefulness of the proposed distributed set-membership filtering scheme.
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