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March 17, 2026International Journal of Robust and Nonlinear Control0 citations

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

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YWYanfeng WangPHPing HePSPeng Shi

Key Points

  • The aim is to design an event-triggered robust extended Kalman filter for stochastic nonlinear systems impacted by packet loss.
  • Constructed an event-triggered robust extended Kalman filter with a prediction-correction structure.
  • Optimized the estimation error covariance matrix upper bound to derive the REKF parameters.
  • Analyzed the REKF performance regarding perturbation attenuation and packet transmission probability.
  • Established sufficient conditions for the exponential boundedness of the REKF estimation error.
  • Conducted two simulation examples to illustrate the effectiveness of the proposed REKF.
  • Found a clear relationship among the perturbation attenuation index, successful packet transmission probability, and event trigger threshold.
  • Demonstrated that the proposed REKF effectively manages estimation errors despite packet loss.
  • Showed that the proposed method maintains exponential boundedness of the estimation error.

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.

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Cite This Study

Wang et al. (2026) studied this question.

synapsesocial.com/papers/69b8f0fddeb47d591b8c5c02https://doi.org/10.1002/rnc.70512
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