IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v488y2025ics0096300324005861.html
   My bibliography  Save this article

Resilient observer-based unified state and fault estimation for nonlinear parabolic PDE systems via fuzzy approach over finite-time interval

Author

Listed:
  • Elayabharath, V.T.
  • Sozhaeswari, P.
  • Tatar, N.
  • Sakthivel, R.
  • Satheesh, T.

Abstract

With the aid of a resilient fuzzy observer, this study delves into the investigation of finite-time state and fault estimation for parabolic-type nonlinear PDE systems described by fuzzy models with faults and external disturbances. Primarily, a fuzzy-dependent observer is built to offer precise estimations of the states and faults simultaneously. Therein, the fluctuations that exhibit random character are taken into account in the observer gain, which enhances the resiliency of the configured fuzzy observer. Meanwhile, the phenomenon of randomly occurring gain fluctuations is effectively characterized by utilizing a random variable that adheres to the Bernoulli distribution. Subsequently, by employing the Lyapunov stability theory and the integral-based Wirtinger's inequality, a set of adequate criteria is obtained in the form of linear matrix inequalities to ascertain that both the state and fault estimation errors are stable in a finite-time with a gratified extended passivity performance index. In the meantime, the observer gain matrices can be obtained by relying on the developed criteria. Ultimately, the simulation results of the Fisher equation are offered to emphasize the superiority of the developed resilient fuzzy observer-based approach.

Suggested Citation

  • Elayabharath, V.T. & Sozhaeswari, P. & Tatar, N. & Sakthivel, R. & Satheesh, T., 2025. "Resilient observer-based unified state and fault estimation for nonlinear parabolic PDE systems via fuzzy approach over finite-time interval," Applied Mathematics and Computation, Elsevier, vol. 488(C).
  • Handle: RePEc:eee:apmaco:v:488:y:2025:i:c:s0096300324005861
    DOI: 10.1016/j.amc.2024.129125
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0096300324005861
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.amc.2024.129125?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Han, Xin-Xin & Wu, Kai-Ning & Ding, Xiaohua, 2020. "Finite-time stabilization for stochastic reaction-diffusion systems with Markovian switching via boundary control," Applied Mathematics and Computation, Elsevier, vol. 385(C).
    2. Zhu, Baopeng & Wang, Yingchun & Zhang, Huaguang & Xie, Xiangpeng, 2021. "Distributed finite-time fault estimation and fault-tolerant control for cyber-physical systems with matched uncertainties," Applied Mathematics and Computation, Elsevier, vol. 403(C).
    3. Xuefeng Zhang & Jin-Xi Zhang & Wenkai Huang & Peng Shi, 2023. "Non-fragile sliding mode observer based fault estimation for interval type-2 fuzzy singular fractional order systems," International Journal of Systems Science, Taylor & Francis Journals, vol. 54(7), pages 1451-1470, May.
    4. Song, Xiaona & Zhang, Renzhi & Song, Shuai & Zhang, Yijun, 2022. "Fuzzy adaptive-event-triggered control for semi-linear parabolic PDE systems with stochastic actuator failures," Applied Mathematics and Computation, Elsevier, vol. 426(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Li, Xing-Yu & Wu, Kai-Ning & Liu, Xiao-Zhen, 2023. "Mittag–Leffler stabilization for short memory fractional reaction-diffusion systems via intermittent boundary control," Applied Mathematics and Computation, Elsevier, vol. 449(C).
    2. Zou, Cong & Li, Bing & Liu, Feiyang & Xu, Bingrui, 2022. "Event-Triggered μ-state estimation for Markovian jumping neural networks with mixed time-delays," Applied Mathematics and Computation, Elsevier, vol. 425(C).
    3. Ye, Hu & Cheng, Peng & Zhang, Xiang & He, Shuping & Zhang, Weidong, 2023. "Event-triggered-based H∞ control for Markov jump cyber-physical systems against denial-of-service attacks," Applied Mathematics and Computation, Elsevier, vol. 451(C).
    4. Mu, Yunfei & Zhang, Huaguang & Yan, Yuqing & Wang, Yingchun, 2023. "A novel design approach to state and fault estimation for interconnected systems using distributed observer," Applied Mathematics and Computation, Elsevier, vol. 449(C).
    5. Zhou, Zepeng & Zhu, Fanglai & Xu, Dezhi & Guo, Shenghui & Zhao, Younan, 2022. "Attack resilient control for vehicle platoon system with full states constraint under actuator faulty scenario," Applied Mathematics and Computation, Elsevier, vol. 419(C).
    6. Peixoto, Márcia L.C. & Coutinho, Pedro H.S. & Nguyen, Anh-Tu & Guerra, Thierry-Marie & Palhares, Reinaldo M., 2024. "Fault estimation for nonlinear parameter-varying time-delayed systems," Applied Mathematics and Computation, Elsevier, vol. 465(C).
    7. Sakthivel, R. & Abinandhitha, R. & Satheesh, T. & Kwon, O.M., 2024. "Hybrid control design for nonlinear chaotic semi-Markov jump systems via fault alarm approach," Chaos, Solitons & Fractals, Elsevier, vol. 189(P1).
    8. Cheng, Xuanrui & Gao, Ming & Huai, Wuxiang & Niu, Yichun & Sheng, Li, 2025. "Fixed-time active fault-tolerant control for dynamical systems with intermittent faults and unknown disturbances," Applied Mathematics and Computation, Elsevier, vol. 486(C).
    9. Ge, Fudong & Chen, YangQuan, 2024. "Event-triggered control for boundary controlled time-fractional diffusion systems with spatially-varying coefficients," Applied Mathematics and Computation, Elsevier, vol. 478(C).
    10. Oliveira, Pedro M. & Palma, Jonathan M. & Lacerda, Márcio J., 2022. "H2 state-feedback control for discrete-time cyber-physical uncertain systems under DoS attacks," Applied Mathematics and Computation, Elsevier, vol. 425(C).
    11. Cheng Peng & Jiaxin Ma & Qiankun Li & Shang Gao, 2022. "Noise-to-State Stability in Probability for Random Complex Dynamical Systems on Networks," Mathematics, MDPI, vol. 10(12), pages 1-11, June.
    12. Zhao, Ailiang & Li, Junmin & Fan, Aili, 2025. "Stabilization for a class of fractional-order nonlinear reaction–diffusion systems with time-varying delay: Event-triggered boundary control approach," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 228(C), pages 23-38.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:apmaco:v:488:y:2025:i:c:s0096300324005861. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/applied-mathematics-and-computation .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.