Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/23222
Title: Recursive State Estimation for Stochastic Complex Networks under Round-Robin Communication Protocol: Handling Packet Disorders
Authors: Liu, D
Wang, Z
Liu, Y
Alsaadi, FE
Alsaadi, FE
Keywords: Recursive state estimation;complex networks;packet disorders;Round-Robin protocol;mean-square boundedness
Issue Date: 7-Jul-2021
Publisher: Institute of Electrical and Electronics Engineers
Citation: D. Liu, Z. Wang, Y. Liu, F. E. Alsaadi and F. E. Alsaadi (2021) Recursive State Estimation for Stochastic Complex Networks under Round-Robin Communication Protocol: Handling Packet Disorders.
Abstract: This paper investigates the recursive state estimation problem for a class of discrete-time stochastic complex networks with packet disorders under Round-Robin (RR) communication protocols. The phenomenon of packet disorders results from the random transmission delays during the signal propagation process due to the unpredictable fluctuations of the network load, and such random delays are modeled by a set of random variables satisfying certain known probability distributions. For the sake of lessening the communication burden and abating the data collisions, the RR protocol is introduced to govern the order of the nodes for data transmission. Under the scheduling of the RR protocol, only one node is allowed to gain the access to the network at each time instant. Then, a recursive estimator is devised to guarantee an upper bound for the estimation error covariance, and then the obtained upper bound is locally minimized by adequately choosing the estimator parameters. Furthermore, the boundedness of estimation error is analyzed in the sense of mean square with the help of stochastic analysis techniques. At last, a simulation example is presented to show the applicability of the proposed estimator design scheme.
URI: http://bura.brunel.ac.uk/handle/2438/23222
DOI: http://dx.doi.org/10.1109/TNSE.2021.3095217
ISSN: http://dx.doi.org/10.1109/TNSE.2021.3095217
2327-4697
Appears in Collections:Dept of Electronic and Computer Engineering Research Papers

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