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H-infinity filtering for T-S fuzzy complex networks subject to sensor saturation via delayed information

机译:H-无穷大滤波,用于通过延迟信息影响传感器饱和的T-S模糊复杂网络

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摘要

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.
机译:本研究解决了传感器饱和的离散时间Takagi-Sugeno模糊复杂网络的分布式滤波问题,其中节点和滤波器通过共享通信网络连接。假设每个节点的输出测量值根据循环调度协议传输到其滤波器。基于非并行分布式补偿策略,构建了分布式滤波器,其中滤波器之间的耦合矩阵可能与节点之间的耦合矩阵不同,滤波器的参数取决于当前和延迟隶属函数。增强滤波误差系统表示为具有时变延迟的离散时间模糊系统。通过应用一种依赖于当前和延迟隶属函数的新型非二次Lyapunov泛函,并结合基于Abel引理的有限和不等式,设计了分布式区域滤波器,保证了增强滤波误差系统的局部和指数稳定性,并满足了性能要求。数值算例说明了所提方法的有效性和保守性。

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