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filtering for T–S fuzzy complex networks subject to sensor saturation via delayed information

filtering for T–S fuzzy complex networks subject to sensor saturation via delayed information

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This study addresses a distributed filtering problem for discrete-time Takagi–Sugeno fuzzy complex networks with sensor saturation, where nodes and filters are connected via a shared communication network. It is supposed that each node's output measurement transmitted to its filter according to Round-Robin scheduling protocol. Based on a non-parallel distributed compensation strategy, distributed filters are constructed, where the coupling matrix between filters could be different from the one between nodes and the parameters of the filters depend on current and delayed membership functions. The augmented filtering error system is represented as a discrete-time fuzzy system with time-varying delays. By applying a novel nonquadratic Lyapunov functional that depends on current and delayed membership functions, and combined with a Abel lemma-based finite-sum inequality, distributed regional filters are designed such that the local and exponential stability of the augmented filtering error system is ensured and the performance requirement is satisfied. Numerical examples illustrate the effectiveness and less conservatism of the proposed method.

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