IDEAS home Printed from https://ideas.repec.org/a/hin/complx/1850737.html
   My bibliography  Save this article

Iterative Learning Fault Estimation Design for Nonlinear System with Random Trial Length

Author

Listed:
  • Li Feng
  • Ke Zhang
  • Yi Chai
  • Shuiqing Xu
  • Zhimin Yang

Abstract

An iterative learning scheme-based fault estimation observer is designed for a class of nonlinear systems with randomly changed trial length. This is achieved by presenting a state observer for monitoring the system state and an iterative learning law for fault estimation in the presence of imprecise system model. An average factor is defined to deal with the lack and redundancy in tracking information caused by random trial length. Via the convergence analysis, sufficient design conditions are developed for estimation of fault signal. The observer gains and iterative learning law indexes are computed by solving the proposed conditions under - constraints. Numerical examples are presented to demonstrate the validity, the effectiveness, and the superiority of this method.

Suggested Citation

  • Li Feng & Ke Zhang & Yi Chai & Shuiqing Xu & Zhimin Yang, 2017. "Iterative Learning Fault Estimation Design for Nonlinear System with Random Trial Length," Complexity, Hindawi, vol. 2017, pages 1-9, November.
    • Handle: RePEc:hin:complx:1850737
    DOI: 10.1155/2017/1850737
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/8503/2017/1850737.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/8503/2017/1850737.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2017/1850737?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
    ---><---

    References listed on IDEAS

    as
    1. Lan Zhou & Jinhua She, 2015. "Design of a robust output-feedback-based modified repetitive-control system," International Journal of Systems Science, Taylor & Francis Journals, vol. 46(5), pages 808-817, April.
    2. Yang, Zhimin & Chai, Yi, 2016. "A survey of fault diagnosis for onshore grid-connected converter in wind energy conversion systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 66(C), pages 345-359.
    3. Lihong Rong & Xiuyan Peng & Biao Zhang, 2017. "A Reduced-Order Fault Detection Filtering Approach for Continuous-Time Markovian Jump Systems with Polytopic Uncertainties," Complexity, Hindawi, vol. 2017, pages 1-14, January.
    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. Mohanapriya, S. & Sweety, C. Antony Crispin & Sakthivel, R. & Parthasarathy, V., 2023. "Disturbance attenuation for neutral Markovian jump systems with multiple delays," Chaos, Solitons & Fractals, Elsevier, vol. 176(C).
    2. Guilherme V. Hollweg & Shahid A. Khan & Shivam Chaturvedi & Yaoyu Fan & Mengqi Wang & Wencong Su, 2023. "Grid-Connected Converters: A Brief Survey of Topologies, Output Filters, Current Control, and Weak Grids Operation," Energies, MDPI, vol. 16(9), pages 1-31, April.
    3. Artigao, Estefania & Martín-Martínez, Sergio & Honrubia-Escribano, Andrés & Gómez-Lázaro, Emilio, 2018. "Wind turbine reliability: A comprehensive review towards effective condition monitoring development," Applied Energy, Elsevier, vol. 228(C), pages 1569-1583.
    4. Yolanda Vidal & Francesc Pozo & Christian Tutivén, 2018. "Wind Turbine Multi-Fault Detection and Classification Based on SCADA Data," Energies, MDPI, vol. 11(11), pages 1-18, November.
    5. Kouadri, Abdelmalek & Hajji, Mansour & Harkat, Mohamed-Faouzi & Abodayeh, Kamaleldin & Mansouri, Majdi & Nounou, Hazem & Nounou, Mohamed, 2020. "Hidden Markov model based principal component analysis for intelligent fault diagnosis of wind energy converter systems," Renewable Energy, Elsevier, vol. 150(C), pages 598-606.
    6. Shrabani Sahu & Sasmita Behera, 2022. "A review on modern control applications in wind energy conversion system," Energy & Environment, , vol. 33(2), pages 223-262, March.
    7. Zahra Yahyaoui & Mansour Hajji & Majdi Mansouri & Kamaleldin Abodayeh & Kais Bouzrara & Hazem Nounou, 2022. "Effective Fault Detection and Diagnosis for Power Converters in Wind Turbine Systems Using KPCA-Based BiLSTM," Energies, MDPI, vol. 15(17), pages 1-19, August.
    8. Liang, Jinping & Zhang, Ke & Al-Durra, Ahmed & Zhou, Daming, 2020. "A novel fault diagnostic method in power converters for wind power generation system," Applied Energy, Elsevier, vol. 266(C).
    9. Yashar Mousavi & Geraint Bevan & Ibrahim Beklan Küçükdemiral & Afef Fekih, 2021. "Maximum Power Extraction from Wind Turbines Using a Fault-Tolerant Fractional-Order Nonsingular Terminal Sliding Mode Controller," Energies, MDPI, vol. 14(18), pages 1-16, September.
    10. Hongqian Wei & Youtong Zhang & Lei Yu & Mengzhu Zhang & Khaled Teffah, 2018. "A New Diagnostic Algorithm for Multiple IGBTs Open Circuit Faults by the Phase Currents for Power Inverter in Electric Vehicles," Energies, MDPI, vol. 11(6), pages 1-14, June.
    11. Tan Yanghong & Zhang Haixia & Zhou Ye, 2018. "A Simple-to-Implement Fault Diagnosis Method for Open Switch Fault in Wind System PMSG Drives without Threshold Setting," Energies, MDPI, vol. 11(10), pages 1-18, September.
    12. Sen Song & Yihua Hu & Kai Ni & Joseph Yan & Guipeng Chen & Huiqing Wen & Xianming Ye, 2018. "Multi-Port High Voltage Gain Modular Power Converter for Offshore Wind Farms," Sustainability, MDPI, vol. 10(7), pages 1-15, June.
    13. Martín Antonio Rodríguez Licea & Francisco Javier Pérez Pinal & Allan Giovanni Soriano Sánchez, 2021. "An Overview on Electric-Stress Degradation Empirical Models for Electrochemical Devices in Smart Grids," Energies, MDPI, vol. 14(8), pages 1-23, April.
    14. Xu Wang & Yanxia Shen, 2019. "Fault Tolerant Control of DFIG-Based Wind Energy Conversion System Using Augmented Observer," Energies, MDPI, vol. 12(4), pages 1-12, February.
    15. Govind, Bala, 2017. "Increasing the operational capability of a horizontal axis wind turbine by its integration with a vertical axis wind turbine," Applied Energy, Elsevier, vol. 199(C), pages 479-494.
    16. Mousavi, Yashar & Bevan, Geraint & Kucukdemiral, Ibrahim Beklan & Fekih, Afef, 2022. "Sliding mode control of wind energy conversion systems: Trends and applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    17. Bakdi, Azzeddine & Kouadri, Abdelmalek & Mekhilef, Saad, 2019. "A data-driven algorithm for online detection of component and system faults in modern wind turbines at different operating zones," Renewable and Sustainable Energy Reviews, Elsevier, vol. 103(C), pages 546-555.

    More about this item

    Statistics

    Access and download statistics

    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:hin:complx:1850737. 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: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.com .

    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.