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  • H∞ filtering for T-S fuzzy networked systems with stochastic multiple delays and sensor faults

    Author(s)
    Xu, Xiaoli
    Yan, Huaicheng
    Zhang, Hao
    Yang, Fuwen
    Griffith University Author(s)
    Yang, Fuwen
    Year published
    2016
    Metadata
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    Abstract
    This paper deals with the problem of H∞ filter design for a class of nonlinear networked systems based on T–S fuzzy model with multiple stochastic time-varying delays, and sensor faults and packet dropouts are considered simultaneously. A sequence of stochastic and independent variables, which obey the Bernoulli distribution, are introduced to depict stochastic time-varying delays. The possible of sensor failure can be described by unrelated random variables taking values on an interval, and the packet dropouts are described as a set of Bernoulli distributed white noises. The approach of piecewise quadratic Lyapunov function ...
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    This paper deals with the problem of H∞ filter design for a class of nonlinear networked systems based on T–S fuzzy model with multiple stochastic time-varying delays, and sensor faults and packet dropouts are considered simultaneously. A sequence of stochastic and independent variables, which obey the Bernoulli distribution, are introduced to depict stochastic time-varying delays. The possible of sensor failure can be described by unrelated random variables taking values on an interval, and the packet dropouts are described as a set of Bernoulli distributed white noises. The approach of piecewise quadratic Lyapunov function is applied to reduce the conservatism. The filter parameters are obtained by solving a set of linear matrix inequalities. Finally, a simulation example is provided to illustrate the effectiveness of the proposed filter design approach.
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    Journal Title
    Neurocomputing
    Volume
    207
    DOI
    https://doi.org/10.1016/j.neucom.2016.05.042
    Subject
    Control Systems, Robotics and Automation
    Information and Computing Sciences
    Engineering
    Psychology and Cognitive Sciences
    Publication URI
    http://hdl.handle.net/10072/99515
    Collection
    • Journal articles

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