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Title: Probability-guaranteed H∞ finite-horizon filtering for a class of nonlinear time-varying systems with sensor saturations
Authors: Hu, J
Wang, Z
Gao, H
Stergioulas, LK
Keywords: Discrete time-varying systems;Probability performance;Finite-horizon;H∞ filtering;Sensor saturation
Issue Date: 2012
Publisher: Elsevier
Citation: Systems & Control Letters, 61(4): 477 - 484, Apr 2012
Abstract: In this paper, the probability-guaranteed H∞ finite-horizon filtering problem is investigated for a class of nonlinear time-varying systems with uncertain parameters and sensor saturations. The system matrices are functions of mutually independent stochastic variables that obey uniform distributions over known finite ranges. Attention is focused on the construction of a time-varying filter such that the prescribed H∞ performance requirement can be guaranteed with probability constraint. By using the difference linear matrix inequalities (DLMIs) approach, sufficient conditions are established to guarantee the desired performance of the designed finite-horizon filter. The time-varying filter gains can be obtained in terms of the feasible solutions of a set of DLMIs that can be recursively solved by using the semi-definite programming method. A computational algorithm is specifically developed for the addressed probability-guaranteed H∞ finite-horizon filtering problem. Finally, a simulation example is given to illustrate the effectiveness of the proposed filtering scheme.
Description: This is the Post-Print version of the Article. The official published version can be accessed from the link below - Copyright @ 2012 Elsevier
ISSN: 0167-6911
Appears in Collections:Publications
Computer Science
Dept of Computer Science Research Papers

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