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Simultaneous disturbance estimation and fault reconstruction using probability density functions

Author

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  • Li, Tao
  • Dai, Zhuxiang
  • Song, Gongfei
  • Du, Haiping

Abstract

A new simultaneous disturbance estimation and fault reconstruction design is studied for stochastic distribution system with actuator faults and output disturbances, where the available information is the measured output probability density function (PDF) of the considered system. Based on this framework, the square-root rational B-spline neural network is applied to model the nonlinear dynamic between PDF and input, where the nonlinearity is assumed to meet the Lipschitz conditions with non-predetermined Lipschitz constants. In addition, a robust descriptor observer is designed to estimate the states and disturbances simultaneously. Meanwhile, the maximum admissible Lipschitz constant is derived via convex optimization. Then, a sliding mode scheme is proposed for the designed observer to reconstruct the actuator faults. Finally, a soil particle gradation control (SPGC) is carried out to show the effectiveness of this way.

Suggested Citation

  • Li, Tao & Dai, Zhuxiang & Song, Gongfei & Du, Haiping, 2019. "Simultaneous disturbance estimation and fault reconstruction using probability density functions," Applied Mathematics and Computation, Elsevier, vol. 362(C), pages 1-1.
    • Handle: RePEc:eee:apmaco:v:362:y:2019:i:c:29
    DOI: 10.1016/j.amc.2019.124561
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    References listed on IDEAS

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    1. Wang, Jing & Hu, Xiaohui & Wei, Yunliang & Wang, Zhen, 2019. "Sampled-data synchronization of semi-Markov jump complex dynamical networks subject to generalized dissipativity property," Applied Mathematics and Computation, Elsevier, vol. 346(C), pages 853-864.
    2. Wang, Jing & Liang, Kun & Huang, Xia & Wang, Zhen & Shen, Hao, 2018. "Dissipative fault-tolerant control for nonlinear singular perturbed systems with Markov jumping parameters based on slow state feedback," Applied Mathematics and Computation, Elsevier, vol. 328(C), pages 247-262.
    3. Yingnan Pan & Guang-Hong Yang, 2017. "Fault detection for interval type-2 fuzzy stochastic systems with D stability constraint," International Journal of Systems Science, Taylor & Francis Journals, vol. 48(1), pages 43-52, January.
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    Cited by:

    1. Li, Tao & Zhang, Zhixuan & Dai, Zhuxiang & Xu, Liuyong, 2022. "Intermediate-estimator-based fault tolerant shape control via PDFs," Applied Mathematics and Computation, Elsevier, vol. 435(C).
    2. Han, Jian & Liu, Xiuhua & Wei, Xinjiang & Zhang, Huifeng & Hu, Xin, 2021. "Adjustable dimension descriptor observer based fault estimation of nonlinear system with unknown input," Applied Mathematics and Computation, Elsevier, vol. 396(C).
    3. Zhu, Jun-Wei & Zhou, Qiao-Qian & Wu, Li-Bing & Xu, Jian-Ming & Wang, Xin, 2021. "Topology reconstruction based fault identification for uncertain multi-agent systems with application to multi-axis motion control system," Applied Mathematics and Computation, Elsevier, vol. 399(C).

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