Event-Triggered Distributed Fusion Estimator for Asynchronous Markov Jump Systems with Correlated Noises and Fading Measurements
In this study, we investigate event-triggered distributed fusion estimation for asynchronous Markov jump systems subject to correlated noises and fading measurements. The measurement noises are interrelated, and they are simultaneously coupled with the system noise. The sensor samples measurements u...
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| Published in | Sensors (Basel, Switzerland) Vol. 24; no. 2; p. 336 |
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| Format | Journal Article |
| Language | English |
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| Abstract | In this study, we investigate event-triggered distributed fusion estimation for asynchronous Markov jump systems subject to correlated noises and fading measurements. The measurement noises are interrelated, and they are simultaneously coupled with the system noise. The sensor samples measurements uniformly, and the sampling rates of the sensors are different. First, the asynchronous system is synchronized at state update points; then, the local filter is obtained. Furthermore, a variance-based event-triggered strategy is introduced between the local estimator and the fusion center to decrease the energy consumption of network communication. Then, a distributed fusion estimation algorithm is proposed using a matrix-weighted fusion criterion. Finally, the effectiveness of the algorithm is verified using computer simulations. |
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| AbstractList | In this study, we investigate event-triggered distributed fusion estimation for asynchronous Markov jump systems subject to correlated noises and fading measurements. The measurement noises are interrelated, and they are simultaneously coupled with the system noise. The sensor samples measurements uniformly, and the sampling rates of the sensors are different. First, the asynchronous system is synchronized at state update points; then, the local filter is obtained. Furthermore, a variance-based event-triggered strategy is introduced between the local estimator and the fusion center to decrease the energy consumption of network communication. Then, a distributed fusion estimation algorithm is proposed using a matrix-weighted fusion criterion. Finally, the effectiveness of the algorithm is verified using computer simulations.In this study, we investigate event-triggered distributed fusion estimation for asynchronous Markov jump systems subject to correlated noises and fading measurements. The measurement noises are interrelated, and they are simultaneously coupled with the system noise. The sensor samples measurements uniformly, and the sampling rates of the sensors are different. First, the asynchronous system is synchronized at state update points; then, the local filter is obtained. Furthermore, a variance-based event-triggered strategy is introduced between the local estimator and the fusion center to decrease the energy consumption of network communication. Then, a distributed fusion estimation algorithm is proposed using a matrix-weighted fusion criterion. Finally, the effectiveness of the algorithm is verified using computer simulations. In this study, we investigate event-triggered distributed fusion estimation for asynchronous Markov jump systems subject to correlated noises and fading measurements. The measurement noises are interrelated, and they are simultaneously coupled with the system noise. The sensor samples measurements uniformly, and the sampling rates of the sensors are different. First, the asynchronous system is synchronized at state update points; then, the local filter is obtained. Furthermore, a variance-based event-triggered strategy is introduced between the local estimator and the fusion center to decrease the energy consumption of network communication. Then, a distributed fusion estimation algorithm is proposed using a matrix-weighted fusion criterion. Finally, the effectiveness of the algorithm is verified using computer simulations. |
| Audience | Academic |
| Author | Lin, Honglei Zhang, Rui |
| AuthorAffiliation | School of Electronic Engineering, Heilongjiang University, Harbin 150080, China; zhangrui_hb@163.com |
| AuthorAffiliation_xml | – name: School of Electronic Engineering, Heilongjiang University, Harbin 150080, China; zhangrui_hb@163.com |
| Author_xml | – sequence: 1 givenname: Rui surname: Zhang fullname: Zhang, Rui – sequence: 2 givenname: Honglei surname: Lin fullname: Lin, Honglei |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/38257429$$D View this record in MEDLINE/PubMed |
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| Keywords | asynchronous Markov jump system correlated noise event-triggered distributed fusion fading measurement |
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| SubjectTerms | Accuracy Algorithms asynchronous Markov jump system Computer simulation Computer-generated environments correlated noise Data transmission distributed fusion Energy consumption Euclidean space event-triggered fading measurement Fault diagnosis Markov analysis Maximum likelihood method Measurement Measuring instruments Sensors Signal processing |
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| Title | Event-Triggered Distributed Fusion Estimator for Asynchronous Markov Jump Systems with Correlated Noises and Fading Measurements |
| URI | https://www.ncbi.nlm.nih.gov/pubmed/38257429 https://www.proquest.com/docview/2918798536 https://www.proquest.com/docview/2917868607 https://pubmed.ncbi.nlm.nih.gov/PMC11154555 https://doaj.org/article/b31363934d214bf4b4413f3cf55a4cb8 |
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