A Dynamic Event-Triggered Transmission Scheme for Distributed Set-Membership Estimation Over Wireless Sensor Networks

This paper is concerned with the distributed set-membership estimation for a discrete-time linear time-varying system over a resource-constrained wireless sensor network under the influence of unknown-but-bounded (UBB) process and measurement noise. Sensors collaborate among themselves by exchanging...

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Veröffentlicht in:IEEE transactions on cybernetics Jg. 49; H. 1; S. 171 - 183
Hauptverfasser: Ge, Xiaohua, Han, Qing-Long, Wang, Zidong
Format: Journal Article
Sprache:Englisch
Veröffentlicht: United States IEEE 01.01.2019
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Computational geometry
Convexity
Discrete time systems
Distributed set-membership estimation
dynamic event-triggered transmission scheme (ETS)
Ellipsoids
Estimation
Kalman filters
Noise measurement
Optimization
Packets (communication)
Parameter estimation
Pollution measurement
recursive convex optimization
Remote sensors
Sensors
Time-varying systems
unknown-but-bounded (UBB) noise
Wireless sensor networks
wireless sensor networks (WSNs)
ISSN:2168-2267, 2168-2275, 2168-2275
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Zusammenfassung:This paper is concerned with the distributed set-membership estimation for a discrete-time linear time-varying system over a resource-constrained wireless sensor network under the influence of unknown-but-bounded (UBB) process and measurement noise. Sensors collaborate among themselves by exchanging local measurements with only neighboring sensors in their sensing ranges. First, a new dynamic event-triggered transmission scheme (ETS) is developed to schedule the transmission of each sensor's local measurement. In contrast with the majority of existing static ETSs, the newly proposed dynamic ETS can result in larger average interevent times and thus less totally released data packets. Second, a criterion for designing desired event-triggered set-membership estimators is derived such that the system's true state always resides in each sensor's bounding ellipsoidal estimation set regardless of the simultaneous presence of UBB process and measurement noise. Third, a recursive convex optimization algorithm is presented to determine optimal ellipsoids as well as the estimator gain parameters and the event triggering weighting matrix parameter. Furthermore, the proposed dynamic ETS is applied to address the distributed set-membership estimation problem for a discrete-time linear time-varying system with a nonlinearity satisfying a sector constraint. Finally, an illustrative example is given to show the effectiveness and advantage of the developed approach.
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ISSN:2168-2267
2168-2275
2168-2275
DOI:10.1109/TCYB.2017.2769722