EconPapers    
Economics at your fingertips  
 

H∞ state estimation for multiplex networks with randomly occurring sensor saturations

Xifen Wu and Haibo Bao

Applied Mathematics and Computation, 2023, vol. 437, issue C

Abstract: This paper investigates the H∞ state estimation problem of multiplex networks (MNs) with sensor saturations. Sensor saturations are first introduced into MNs to study the state estimation of MNs. The aim of this paper is to design a set of H∞ state estimators to estimate the state of MNs through the available output measurements. The basic requirements of this kind of estimators are that the dynamics of estimation error is exponentially mean-square stable and meets the H∞ performance requirement. The sufficient conditions are established to meet these two basic requirements. In this paper, the normal operation, sensor saturations and missing measurements of MNs are described in a unified way by means of Kronecker delta function, and a new measurement model is proposed to describe these random events. This model can clearly and intuitively explain any combination of the normal operation, sensor saturations and missing measurements only by changing the probability of their random occurrence. Next, the estimator gain of the designed estimators for MNs can be easily obtained by taking advantage of solving certain matrix inequalities. Through a series of analysis, it is found that there is an important relationship between the inter-layer couplings of MNs and the estimation time of MNs. Finally, the effectiveness of the proposed state estimation approach is verified by numerical simulations.

Keywords: Multiplex networks; H∞ state estimation; Sensor saturations; Synchronization; Exponentially mean-square stable (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0096300322006129
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:437:y:2023:i:c:s0096300322006129

DOI: 10.1016/j.amc.2022.127538

Access Statistics for this article

Applied Mathematics and Computation is currently edited by Theodore Simos

More articles in Applied Mathematics and Computation from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2025-03-19
Handle: RePEc:eee:apmaco:v:437:y:2023:i:c:s0096300322006129