Reliable filtering for fuzzy Markov stochastic systems with sensor failures and packet dropouts
- Author(s): Renquan Lu 2 ; Hui Peng 1 ; Shuang Liu 1 ; Yong Xu 2 ; Xiao-Meng Li 1
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View affiliations
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Affiliations:
1:
The Guangdong Key Laboratory of IoT Information Technology, School of Automation , Guangdong University of Technology , Guangzhou 510006 , People's Republic of China ;
2: The Key Laboratory for IoT and Information Fusion Technology of Zhejiang , Institute of Information and Control, Hangzhou Dianzi University , Hangzhou 310018 , People's Republic of China
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Affiliations:
1:
The Guangdong Key Laboratory of IoT Information Technology, School of Automation , Guangdong University of Technology , Guangzhou 510006 , People's Republic of China ;
- Source:
Volume 11, Issue 14,
22
September
2017,
p.
2195 – 2203
DOI: 10.1049/iet-cta.2017.0361 , Print ISSN 1751-8644, Online ISSN 1751-8652
This study addresses the filter design issue for fuzzy Markov stochastic systems with sensor failures and packet dropouts. A more general failure model is used for Markov systems to better describe the sensor failures, and the packet dropouts are assumed to obey a series of Bernoulli processes which are formed into a diagonal matrix. Sufficient condition is established to guarantee that the filtering error system is stochastically stable and achieves the given performance. The parameters of the filter are then derived by solving linear matrix inequalities. Simulation results are given to demonstrate the usefulness and availability of the proposed method.
Inspec keywords: fuzzy systems; stochastic systems; linear matrix inequalities; filtering theory; Markov processes; sensors
Other keywords: linear matrix inequalities; general failure model; fuzzy Markov stochastic systems; sensor failures; filter design issue; LMI; Bernoulli processes; diagonal matrix; I2-l∞ filtering; filtering error system; packet dropouts
Subjects: Algebra; Fuzzy control; Markov processes; Time-varying control systems; Transducers and sensing devices
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