Quantized feedback control of fuzzy Markov jump systems

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dc.contributor.authorZhang, M.
dc.contributor.authorShi, P.
dc.contributor.authorMa, L.
dc.contributor.authorCai, J.
dc.contributor.authorSu, H.
dc.date.issued2019
dc.description.abstractThis paper addresses the problem of quantized feedback control of nonlinear Markov jump systems (MJSs). The nonlinear plant is represented by a class of fuzzy MJSs with time-varying delay based on a Takagi-Sugeno fuzzy model. The quantized signal is utilized for control purpose and the sector bound approach is exploited to deal with quantization errors. By constructing a Lyapunov function which depends both on mode information and fuzzy basis functions, the reciprocally convex approach is used to derive the criterion which is able to ensure the stochastic stability with a predefined l₂ - l(∞) performance of the resulting closed-loop system. The design of the quantized feedback controller is then converted to a convex optimization problem, which can be handled through the linear matrix inequality technique. Finally, a simulation example is presented to verify the effectiveness and practicability of the proposed new design techniques.
dc.description.statementofresponsibilityMeng Zhang, Peng Shi, Longhua Ma, Jianping Cai, and Hongye Su
dc.identifier.citationIEEE Transactions on Cybernetics, 2019; 49(9):3375-3384
dc.identifier.doi10.1109/TCYB.2018.2842434
dc.identifier.issn2168-2267
dc.identifier.issn2168-2275
dc.identifier.orcidShi, P. [0000-0001-6295-0405] [0000-0001-8218-586X] [0000-0002-0864-552X] [0000-0002-1358-2367] [0000-0002-5312-5435]
dc.identifier.urihttps://hdl.handle.net/2440/132168
dc.language.isoen
dc.publisherIEEE
dc.relation.grant61573322
dc.relation.grant61633019
dc.relation.grant61272020
dc.relation.grant61773131
dc.relation.grantU1509217
dc.relation.granthttp://purl.org/au-research/grants/arc/DP170102644
dc.rights© 2018 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information.
dc.source.urihttps://doi.org/10.1109/tcyb.2018.2842434
dc.subjectFuzzy systems; l₂ − l∞ performance; Markov jump systems (MJSs); quantization; time-varying delay
dc.titleQuantized feedback control of fuzzy Markov jump systems
dc.typeJournal article
pubs.publication-statusPublished

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