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Finite-time filtering for non-linear stochastic systems with partially known transition jump rates

Luan, Xiaoli and Liu, Fei and Shi, Peng (2010) Finite-time filtering for non-linear stochastic systems with partially known transition jump rates. IET Control Theory and Applications, 4 (5). pp. 735-745. ISSN 1751-8644

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Abstract

This study is concerned with the problem of robust finite-time filtering for a class of non-linear Markov jump systems (MJSs) with partially known information on the transition jump rates. The non-linearities in the system are parameterised by multilayer neural networks. Our attention is focused on the design of a modedependent full-order H∞ filter to ensure the finite-time boundedness of the filtering error system and a prescribed H∞ attenuation level for all admissible uncertainties and approximation errors of the networks. Sufficient conditions of filtering design are developed in terms of solvability of a set of linear matrix inequalities. A tunnel diode circuit is used to show the effectiveness and potentials of the proposed techniques.

Item Type: Article
Uncontrolled Keywords: ResPubID19954, control nonlinearities, filtering theory, linear matrix inequalities, neural nets, neurocontrollers, nonlinear control systems, stochastic systems
Subjects: Faculty/School/Research Centre/Department > Institute for Logistics and Supply Chain Management (ILSCM)
FOR Classification > 0802 Computation Theory and Mathematics
SEO Classification > 970108 Expanding Knowledge in the Information and Computing Sciences
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Depositing User: VUIR
Date Deposited: 20 Dec 2011 22:25
Last Modified: 23 Mar 2015 04:12
URI: http://vuir.vu.edu.au/id/eprint/7456
DOI: 10.1049/iet-cta.2009.0014
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Citations in Scopus: 50 - View on Scopus

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