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)
Year published
2016
Metadata
Show full item recordAbstract
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 ...
View more >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.
View less >
View more >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.
View less >
Journal Title
Neurocomputing
Volume
207
Subject
Control Systems, Robotics and Automation
Information and Computing Sciences
Engineering
Psychology and Cognitive Sciences