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The distributed fault diagnosis for nonlinear complex dynamical networks based on σ-detection criterion

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  • Dong, Qian
  • Yuan, Wenying
  • Tong, Tianchi
  • Sun, Jinsheng

Abstract

The actuator fault diagnosis problem of nonlinear complex dynamical networks with stochastic noise is investigated. Firstly, a local estimation based on a priori knowledge and measurement output is designed to estimate state for each node. A sufficient condition is derived such that the estimation error is stable and the estimation gain matrix is obtained in fault-free case by applying the stability theory. Secondly, considering additive actuator fault in presence of process and measurement noises, the residual signal based on estimation error is designed to detect faults and locate them. Thirdly, the threshold is acquired by applying the covariance matrix of estimation error. A fault detection and isolation logic is designed via the σ-detection criterion. Finally, two different examples are designed to verify the effectiveness of the designed actuator fault detection and isolation scheme.

Suggested Citation

  • Dong, Qian & Yuan, Wenying & Tong, Tianchi & Sun, Jinsheng, 2024. "The distributed fault diagnosis for nonlinear complex dynamical networks based on σ-detection criterion," Chaos, Solitons & Fractals, Elsevier, vol. 186(C).
    • Handle: RePEc:eee:chsofr:v:186:y:2024:i:c:s0960077924007951
    DOI: 10.1016/j.chaos.2024.115243
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    References listed on IDEAS

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    5. Yuan, Wenying & Tong, Tianchi & Dong, Qian & Sun, Jinsheng, 2024. "Stealthy FDI attacks on modified Kalman filtering in complex networks with non-Gaussian-Lévy noise," Chaos, Solitons & Fractals, Elsevier, vol. 179(C).
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