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access icon free 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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  • 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
© The Institution of Engineering and Technology
Received 03/04/2017, Accepted 29/04/2017, Published 09/05/2017

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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