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Title: Robust H∞ filtering for markovian jump systems with randomly occurring nonlinearities and sensor saturation: The finite-horizon case
Authors: Dong, H
Wang, Z
Gao, H
Keywords: Discrete time-varying systems
Markovian jumping parameters
Randomly occurring nonlinearities
Robust H∞ filtering
Sensor saturation
Publication Date: 2011
Publisher: IEEE
Citation: IEEE Transactions on Signal Processing, 59(7): 3048 - 3057, Jul 2011
Abstract: This paper addresses the robust H∞ filtering problem for a class of discrete time-varying Markovian jump systems with randomly occurring nonlinearities and sensor saturation. Two kinds of transition probability matrices for the Markovian process are considered, namely, the one with polytopic uncertainties and the one with partially unknown entries. The nonlinear disturbances are assumed to occur randomly according to stochastic variables satisfying the Bernoulli distributions. The main purpose of this paper is to design a robust filter, over a given finite-horizon, such that the H∞ disturbance attenuation level is guaranteed for the time-varying Markovian jump systems in the presence of both the randomly occurring nonlinearities and the sensor saturation. Sufficient conditions are established for the existence of the desired filter satisfying the H∞ performance constraint in terms of a set of recursive linear matrix inequalities. Simulation results demonstrate the effectiveness of the developed filter design scheme.
Description: This article is posted with the permission of IEEE - Copyright @ 2011 IEEE
Sponsorship: This work was supported in part by the National Natural Science Foundation of China under Grants 61028008, 60825303, and 61004067, National 973 Project under Grant 2009CB320600, the Key Laboratory of Integrated Automation for the Process Industry (Northeastern University) from the Ministry of Education of China, the Engineering and Physical Sciences Research Council (EPSRC) of the U.K., under Grant GR/S27658/01, the Royal Society of the U.K., and the Alexander von Humboldt Foundation of Germany.
ISSN: 1053-587X
Appears in Collections:Publications
Computer Science
Dept of Computer Science Research Papers

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