Event‐Triggered Robust Extended Kalman Filtering for Stochastic Nonlinear Systems Subject to Packet Loss

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Authors: Yanfeng Wang, Ping He, Peng Jia Shi
Cited by: 0
References: 40

Abstract

ABSTRACT In this paper, the event‐triggered robust extended Kalman filter (REKF) design problem for stochastic nonlinear systems subject to packet loss is investigated. Firstly, an event‐triggered REKF with the prediction‐correction structure is constructed to derive the estimation error expression considering packet loss. Secondly, the REKF parameter is obtained by optimizing the estimation error covariance matrix upper bound. The performance of REKF is analyzed and the relationship among the perturbation attenuation performance index, the successful packet transmission probability and the event trigger threshold is obtained. Thirdly, sufficient conditions for the exponential boundedness of the REKF estimation error have been established. Finally, two simulation examples illustrate that the proposed REKF is effective.

Fields of Study & Subjects

Stability and Control of Uncertain Systems Target Tracking and Data Fusion in Sensor Networks Control Systems and Identification

Publication details

Journal / source
International Journal of Robust and Nonlinear Control
Volume
36
Issue
10
Pages
5306–5317
Publication date
15 March 2026
Language
EN