Remote State Estimation for Jump Markov Nonlinear Systems: A Stochastic Event-Triggered Approach

Weihao Song, Jianan Wang*, Dandan Wang, Chunyan Wang, Jiayuan Shan

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

This paper investigates the remote state estimation issue for the jump Markov nonlinear systems (JMNLSs) with the stochastic event-triggered transmission strategy. For the purpose of saving the scarce network resources, the stochastic event-triggered communication is employed to cut down the number of measurement transmission. The interacting multiple model (IMM) scheme is incorporated due to its strength in alleviating computational burden encountered in the multiple model state estimation problem. In addition, the estimated measurement is utilized to update the mode probability in IMM-based filter when the current measurement is not available to the remote estimators. The proposed algorithm is applied in a two-dimensional maneuvering target tracking problem and the simulation results are presented, which validates the usefulness of the developed scheme.

Original languageEnglish
Title of host publication7th International Conference on Control, Decision and Information Technologies, CoDIT 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1099-1104
Number of pages6
ISBN (Electronic)9781728159539
DOIs
Publication statusPublished - 29 Jun 2020
Event7th International Conference on Control, Decision and Information Technologies, CoDIT 2020 - Prague, Czech Republic
Duration: 29 Jun 20202 Jul 2020

Publication series

Name7th International Conference on Control, Decision and Information Technologies, CoDIT 2020

Conference

Conference7th International Conference on Control, Decision and Information Technologies, CoDIT 2020
Country/TerritoryCzech Republic
CityPrague
Period29/06/202/07/20

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