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• W2906353487 abstract "This work is concerned with robust filtering of nonlinear sampled-data systems with and without exact discrete-time models. A linear matrix inequality (LMI) based approach is proposed for the design of robust $H_{infty}$ observers for a class of Lipschitz nonlinear systems. Two type of systems are considered, Lipschitz nonlinear discrete-time systems and Lipschitz nonlinear sampled-data systems with Euler approximate discrete-time models. Observer convergence when the exact discrete-time model of the system is available is shown. Then, practical convergence of the proposed observer is proved using the Euler approximate discrete-time model. As an additional feature, maximizing the admissible Lipschitz constant, the solution of the proposed LMI optimization problem guaranties robustness against some nonlinear uncertainty. The robust H_infty observer synthesis problem is solved for both cases. The maximum disturbance attenuation level is achieved through LMI optimization. At the end, a path to extending the results to higher-order approximate discretizations is provided." @default.
• W2906353487 created "2019-01-01" @default.
• W2906353487 creator A5018683464 @default.
• W2906353487 creator A5051014376 @default.
• W2906353487 date "2018-12-23" @default.
• W2906353487 modified "2023-09-27" @default.
• W2906353487 title "Nonlinear Robust Filtering of Sampled-Data Dynamical Systems." @default.
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• W2906353487 hasPublicationYear "2018" @default.
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