Robust reliable dissipative filtering for Markovian jump nonlinear systems with uncertainties | Zendy

Sakthivel Rathinasamy | Zendy; Sathishkumar M. | Zendy; Mathiyalagan Kalidass | Zendy; Marshal Anthoni S. | Zendy

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Robust reliable dissipative filtering for Markovian jump nonlinear systems with uncertainties

Author(s) -

Sakthivel Rathinasamy,

Sathishkumar M.,

Mathiyalagan Kalidass,

Marshal Anthoni S.

Publication year - 2017

Publication title -

international journal of adaptive control and signal processing

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.73

H-Index - 66

eISSN - 1099-1115

pISSN - 0890-6327

DOI - 10.1002/acs.2680

Subject(s) - dissipative system , control theory (sociology) , filter (signal processing) , nonlinear system , mathematics , linear matrix inequality , filter design , polytope , passivity , filtering problem , lyapunov function , matrix (chemical analysis) , set (abstract data type) , computer science , mathematical optimization , control (management) , physics , engineering , artificial intelligence , materials science , discrete mathematics , quantum mechanics , electrical engineering , composite material , computer vision , programming language

Summary This paper investigates the problem of robust reliable dissipative filtering for a class of Markovian jump nonlinear systems with uncertainties and time‐varying transition probability matrix described by a polytope. Our main attention is focused on the design of a reliable dissipative filter performance for the filtering error system such that the resulting error system is stochastically stable and strictly ( Q , S , R ) dissipative. By introducing a novel augmented Lyapunov–Krasovskii functional, a new set of sufficient conditions is obtained for the existence of reliable dissipative filter design in terms of linear matrix inequalities (LMIs). More precisely, a sufficient LMI condition is derived for reliable dissipative filtering that unifies the conditions for filtering with passivity and H ∞ performances. Moreover, the filter gains are characterized in terms of solution to a set of linear matrix inequalities. Finally, two numerical examples are provided to demonstrate the effectiveness and potential of the proposed design technique. Copyright © 2016 John Wiley & Sons, Ltd.

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