Distributed Resilient Fusion Filtering for Nonlinear Systems with Random Sensor Delays: Optimized Algorithm Design and Boundedness Analysis

This paper is concerned with the distributed resilient fusion filtering (DRFF) problem for a class of time-varying multi-sensor nonlinear stochastic systems (MNSSs) with random sensor delays (RSDs). The phenomenon of the RSDs is modeled by a set of random variables with certain statistical features....

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Vydané v:Journal of systems science and complexity Ročník 36; číslo 4; s. 1423 - 1442
Hlavní autori: Hu, Jun, Hu, Zhibin, Dong, Hongli, Liu, Hongjian
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Berlin/Heidelberg Springer Berlin Heidelberg 01.08.2023
Springer Nature B.V
Predmet:
Algorithms
Complex Systems
Control
Design optimization
Filtration
Mathematics
Mathematics and Statistics
Mathematics of Computing
Nonlinear systems
Operations Research/Decision Theory
Perturbation
Random variables
Sensors
Statistics
Stochastic systems
Systems Theory
Taylor series
Upper bounds
matrix-weighted fusion
nonlinear time-varying systems
random sensor delays
Distributed resilient fusion filtering
ISSN:1009-6124, 1559-7067
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Popis
Shrnutí:This paper is concerned with the distributed resilient fusion filtering (DRFF) problem for a class of time-varying multi-sensor nonlinear stochastic systems (MNSSs) with random sensor delays (RSDs). The phenomenon of the RSDs is modeled by a set of random variables with certain statistical features. In addition, the nonlinear function is handled via Taylor expansion in order to deal with the nonlinear fusion filtering problem. The aim of the addressed issue is to propose a DRFF scheme for MNSSs such that, for both RSDs and estimator gain perturbations, certain upper bounds of estimation error covariance (EEC) are given and locally minimized at every sample time. In the light of the obtained local filters, a new DRFF algorithm is developed via the matrix-weighted fusion method. Furthermore, a sufficient condition is presented, which can guarantee that the local upper bound of the EEC is bounded. Finally, a numerical example is provided, which can show the usefulness of the developed DRFF approach.
Bibliografia:ObjectType-Article-1
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ObjectType-Feature-2
content type line 14
ISSN:1009-6124
1559-7067
DOI:10.1007/s11424-023-2183-z