Probabilistic-Constrained Distributed Set-Membership Estimation Over Sensor Networks: A Dynamic Periodic Event-Triggered Approach

This article is concerned with the event-triggered probabilistic-constrained distributed set-membership estimation problem for a discrete-time nonlinear system over sensor networks. For saving communication resource, a novel discrete-time dynamic periodic event-triggered mechanism (ETM) is first dev...

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Veröffentlicht in:	IEEE transactions on network science and engineering Jg. 9; H. 6; S. 4444 - 4457
Hauptverfasser:	Xie, Yuhan, Ding, Sanbo, Yang, Feisheng, Wang, Leimin, Xie, Xiangpeng
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 01.11.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Co-design Computational geometry Constraints Convexity Discrete time systems discrete-time dynamic periodic event-triggered mechanism distributed set-membership estimation Ellipsoids Estimation Network topology Nonlinear systems Optimization probabilistic constraints Probabilistic logic Probability theory Robot sensing systems sensor networks Sensors Sparse matrices Statistical analysis
ISSN:	2327-4697, 2334-329X
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Abstract	This article is concerned with the event-triggered probabilistic-constrained distributed set-membership estimation problem for a discrete-time nonlinear system over sensor networks. For saving communication resource, a novel discrete-time dynamic periodic event-triggered mechanism (ETM) is first developed for the sensor network. Under the proposed method, the sensor node calculates the ETM in a periodic manner and the threshold is adjusted dynamically. Thereafter, a distributed set-membership estimator is constructed, and a probability-based estimated ellipsoidal constraint is put forward to acquire a more flexible set-membership estimation algorithm. Simultaneously, an auxiliary-function-dependent approach is proposed to derive the criterion for the co-design of the probabilistic-constrained set-membership estimator and the event-triggered parameter such that the system states reside in the estimated ellipsoid with a pre-specified probability. The auxiliary function is constructed in a piecewise style aiming to deal with the sawtooth constraint of sampling signals. Furthermore, a recursive convex optimization algorithm with regard to the estimated ellipsoid is presented. Finally, a simulation example is employed to verify the validity of the developed method.
AbstractList	This article is concerned with the event-triggered probabilistic-constrained distributed set-membership estimation problem for a discrete-time nonlinear system over sensor networks. For saving communication resource, a novel discrete-time dynamic periodic event-triggered mechanism (ETM) is first developed for the sensor network. Under the proposed method, the sensor node calculates the ETM in a periodic manner and the threshold is adjusted dynamically. Thereafter, a distributed set-membership estimator is constructed, and a probability-based estimated ellipsoidal constraint is put forward to acquire a more flexible set-membership estimation algorithm. Simultaneously, an auxiliary-function-dependent approach is proposed to derive the criterion for the co-design of the probabilistic-constrained set-membership estimator and the event-triggered parameter such that the system states reside in the estimated ellipsoid with a pre-specified probability. The auxiliary function is constructed in a piecewise style aiming to deal with the sawtooth constraint of sampling signals. Furthermore, a recursive convex optimization algorithm with regard to the estimated ellipsoid is presented. Finally, a simulation example is employed to verify the validity of the developed method.
Author	Xie, Yuhan Wang, Leimin Yang, Feisheng Xie, Xiangpeng Ding, Sanbo
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SubjectTerms	Algorithms Co-design Computational geometry Constraints Convexity Discrete time systems discrete-time dynamic periodic event-triggered mechanism distributed set-membership estimation Ellipsoids Estimation Network topology Nonlinear systems Optimization probabilistic constraints Probabilistic logic Probability theory Robot sensing systems sensor networks Sensors Sparse matrices Statistical analysis
Title	Probabilistic-Constrained Distributed Set-Membership Estimation Over Sensor Networks: A Dynamic Periodic Event-Triggered Approach
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