Robust reliable dissipative filtering for Markovian jump nonlinear systems with uncertainties |
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| Authors: | Rathinasamy Sakthivel M. Sathishkumar Kalidass Mathiyalagan S. Marshal Anthoni |
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| Affiliation: | 1. Department of Mathematics, Sri Ramakrishna Institute of Technology, Coimbatore – 641 010, India;2. Department of Mathematics, Sungkyunkwan University, Suwon, Korea;3. Department of Mathematics, Anna University ‐ Regional Campus, Coimbatore – 641046, India |
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| Abstract: | 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  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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| Keywords: | Markovian jump nonlinear systems reliable dissipative filter polytope uncertainties |
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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.