Filtering for Discrete-Time Stochastic Systems with Nonlinear Sensor and Time-Varying Delay | Zendy

Mingang Hua | Zendy; Pei Cheng | Zendy; Juntao Fei | Zendy; Jianyong Zhang | Zendy; Junfeng Chen | Zendy

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Filtering for Discrete-Time Stochastic Systems with Nonlinear Sensor and Time-Varying Delay

Author(s) -

Mingang Hua,

Pei Cheng,

Juntao Fei,

Jianyong Zhang,

Junfeng Chen

Publication year - 2013

Publication title -

international journal of stochastic analysis

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.19

H-Index - 28

eISSN - 2090-3340

pISSN - 2090-3332

DOI - 10.1155/2013/306707

Subject(s) - mathematics , discrete time and continuous time , control theory (sociology) , nonlinear system , linear matrix inequality , stability (learning theory) , class (philosophy) , filtering problem , lyapunov function , mathematical optimization , computer science , kalman filter , control (management) , statistics , physics , quantum mechanics , artificial intelligence , machine learning , extended kalman filter

The filtering problem for a class of discrete-time stochastic systems with nonlinear sensor and time-varying delay is investigated. By using the Lyapunov stability theory, sufficient conditions are proposed to guarantee the asymptotical stablity with an prescribe performance level of the filtering error systems. These conditions are dependent on the lower and upper bounds of the discrete time-varying delays and are obtained in terms of a linear matrix inequality (LMI). Finally, two numerical examples are provided to illustrate the effectiveness of the proposed methods

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