4.8 Article

Finite-Time Dynamic Event-Triggered Distributed H∞ Filtering for T-S Fuzzy Systems

Journal

IEEE TRANSACTIONS ON FUZZY SYSTEMS
Volume 30, Issue 7, Pages 2476-2486

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TFUZZ.2021.3086560

Keywords

Dynamic event-triggered mechanism (ETM); finite-time horizon; piecewise Takagi-Sugeno (T-S) fuzzy distributed H-infinity filtering; sensor saturation; T-S fuzzy system

Funding

  1. National Natural Science Foundation of China [61922063, 61773289]
  2. Shanghai Natural Science Foundation [19ZR1461400l]
  3. Shanghai Shuguang Project [18SG18]
  4. Fundamental Research Funds for the Central Universities

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This article investigates the problem of distributed H-infinity filtering in finite-time horizon for a class of Takagi-Sugeno (T-S) fuzzy systems with sensor saturation and unknown bounded noise. A dynamic event-triggered mechanism (ETM) is proposed to consider the network bandwidth limitation. By applying the partition approach to address the asynchronous problem of premise variables induced by ETM, a novel piecewise T-S fuzzy distributed H-infinity filtering is derived. The sufficient conditions for the finite-time H-infinity performance of the estimation error system are given through constructing the Lyapunov function. Furthermore, the optimal problem of disturbance attenuate parameter gamma is solved to minimize the interference from disturbance to distributed filtering. A simulation example is conducted to verify the effectiveness of the proposed algorithm.
In this article, the problem of the distributed H-infinity filtering in finite-time horizon is investigated for a class of Takagi-Sugeno (T-S) fuzzy systems with sensor saturation and unknown bounded noise. Considering the network bandwidth limitation, a dynamic event-triggered mechanism (ETM) is proposed. Due to an asynchronous problem of premise variables induced by the dynamic ETM, the partition approach is applied. Under the partition region, a novel piecewise T-S fuzzy distributed H-infinity filtering is derived. By constructing the Lyapunov function, sufficient conditions for the finite-time H-infinity performance of the estimation error system are given. Furthermore, to minimize the interference from disturbance to distributed filtering, the optimal problem of disturbance attenuate parameter gamma is solved. Finally, a simulation example is presented to verify the effectiveness of the proposed algorithm.

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