IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v359y2019icp433-455.html
   My bibliography  Save this article

Fault tolerant control of UMV based on sliding mode output feedback

Author

Listed:
  • Hao, Li-Ying
  • Yu, Ying
  • Li, Hui

Abstract

This paper designs the robust fault tolerant controller for unmanned marine vehicle (UMV) systems with thruster faults and external disturbances via sliding mode output feedback. A comprehensive and unified fault model including thruster partial, complete and stuck faults is built for the first time. Based on input matrix full-rank decomposition technique and H∞ technique, a sufficient condition of sliding mode in the form of linear matrix inequality (LMI) is given. Then taking advantage of adaptive mechanism, a nonlinear discontinuous control term and an output feedback controller are aimed to reduce the oscillation amplitudes of the yaw velocity error and the yaw angle. Compared with the existing methods, the general faults including time-varying stuck fault can be dealt with. Eventually, the comparative simulation results have demonstrated the effectiveness and feasibility of the presented strategy in this paper.

Suggested Citation

  • Hao, Li-Ying & Yu, Ying & Li, Hui, 2019. "Fault tolerant control of UMV based on sliding mode output feedback," Applied Mathematics and Computation, Elsevier, vol. 359(C), pages 433-455.
    • Handle: RePEc:eee:apmaco:v:359:y:2019:i:c:p:433-455
    DOI: 10.1016/j.amc.2019.04.069
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0096300319303571
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.amc.2019.04.069?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. Lee, Tae H. & Park, Ju H. & Jung, Hoyoul, 2018. "Network-based H∞ state estimation for neural networks using imperfect measurement," Applied Mathematics and Computation, Elsevier, vol. 316(C), pages 205-214.
    2. Li, Jian & Pan, Kunpeng & Su, Qingyu, 2019. "Sensor fault detection and estimation for switched power electronics systems based on sliding mode observer," Applied Mathematics and Computation, Elsevier, vol. 353(C), pages 282-294.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Meng, Xin & Zhai, Ding & Fu, Zhumu & Xie, Xiangpeng, 2020. "Adaptive fault tolerant control for a class of switched nonlinear systems with unknown control directions," Applied Mathematics and Computation, Elsevier, vol. 370(C).
    2. Xia, Yude & Wang, Jing & Meng, Bo & Chen, Xiangyong, 2020. "Further results on fuzzy sampled-data stabilization of chaotic nonlinear systems," Applied Mathematics and Computation, Elsevier, vol. 379(C).

    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. 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.
    2. Jiao, Shiyu & Shen, Hao & Wei, Yunliang & Huang, Xia & Wang, Zhen, 2018. "Further results on dissipativity and stability analysis of Markov jump generalized neural networks with time-varying interval delays," Applied Mathematics and Computation, Elsevier, vol. 336(C), pages 338-350.
    3. 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.
    4. Ma, Zheng & Song, Jiasheng & Zhou, Jianping, 2022. "Reliable event-based dissipative filter design for discrete-time system with dynamic quantization and sensor fault," Applied Mathematics and Computation, Elsevier, vol. 418(C).
    5. Tan, Guoqiang & Wang, Zhanshan & Li, Cong, 2020. "H∞ performance state estimation of delayed static neural networks based on an improved proportional-integral estimator," Applied Mathematics and Computation, Elsevier, vol. 370(C).
    6. Ma, Zhen-Lei & Li, Xiao-Jian, 2022. "Data-driven fault detection for large-scale network systems: A mixed optimization approach," Applied Mathematics and Computation, Elsevier, vol. 426(C).
    7. Li, Xin & Wei, Guoliang & Ding, Derui, 2021. "Distributed resilient interval estimation for sensor networks under aperiodic denial-of-service attacks and adaptive event-triggered protocols," Applied Mathematics and Computation, Elsevier, vol. 409(C).
    8. Han, Yunrui & Zhao, Ying & Wang, Peng, 2021. "Finite-time rate anti-bump switching control for switched systems," Applied Mathematics and Computation, Elsevier, vol. 401(C).
    9. Hu, Jun & Li, Jiaxing & Kao, Yonggui & Chen, Dongyan, 2022. "Optimal distributed filtering for nonlinear saturated systems with random access protocol and missing measurements: The uncertain probabilities case," Applied Mathematics and Computation, Elsevier, vol. 418(C).
    10. Li, Yueyang & Song, Xinmin & Zhang, Zhijie & Zhao, Dong & Wang, Zhonghua, 2019. "H∞ deconvolution filter design for uncertain linear discrete time-variant systems: A Krein space approach," Applied Mathematics and Computation, Elsevier, vol. 361(C), pages 131-143.
    11. Wang, Jun & Shi, Kaibo & Huang, Qinzhen & Zhong, Shouming & Zhang, Dian, 2018. "Stochastic switched sampled-data control for synchronization of delayed chaotic neural networks with packet dropout," Applied Mathematics and Computation, Elsevier, vol. 335(C), pages 211-230.
    12. Yang, Haijiao & Ye, Dan, 2020. "Time-varying formation tracking control for high-order nonlinear multi-agent systems in fixed-time framework," Applied Mathematics and Computation, Elsevier, vol. 377(C).
    13. Shi, Xuanxuan & Shen, Mouquan, 2019. "A new approach to feedback feed-forward iterative learning control with random packet dropouts," Applied Mathematics and Computation, Elsevier, vol. 348(C), pages 399-412.
    14. Zheng, Wei & Zhang, Zhiming & Sun, Fuchun & Lam, Hak Keung & Wen, Shuhuan, 2022. "Stability analysis and robust controller design for systems with mixed time-delays and stochastic nonlinearity via cone complementarity linearization," Applied Mathematics and Computation, Elsevier, vol. 430(C).
    15. Fu, Haijing & Li, Jiahui & Han, Fei & Hou, Nan & Dong, Hongli, 2021. "Outlier-resistant bserver-based H∞ PID control under stochastic communication protocol," Applied Mathematics and Computation, Elsevier, vol. 411(C).
    16. Zhou, Yu & Pan, Yingnan & Li, Shubo & Liang, Hongjing, 2020. "Event-triggered cooperative containment control for a class of uncertain non-identical networks," Applied Mathematics and Computation, Elsevier, vol. 375(C).
    17. Zeng, Hong-Bing & Zhai, Zheng-Liang & He, Yong & Teo, Kok-Lay & Wang, Wei, 2020. "New insights on stability of sampled-data systems with time-delay," Applied Mathematics and Computation, Elsevier, vol. 374(C).
    18. Xiong, Jun & Chang, Xiao-Heng & Yi, Xiaojian, 2018. "Design of robust nonfragile fault detection filter for uncertain dynamic systems with quantization," Applied Mathematics and Computation, Elsevier, vol. 338(C), pages 774-788.
    19. Malik, Saddam Hussain & Tufail, Muhammad & Rehan, Muhammad & Ahmed, Shakeel, 2022. "State and output feedback local control schemes for nonlinear discrete-time 2-D Roesser systems under saturation, quantization and slope restricted input," Applied Mathematics and Computation, Elsevier, vol. 423(C).
    20. Fu, Teng & Zhou, Yusheng, 2022. "Stabilization of switched time-delay systems with only unstable subsystems: a new approach based on a vibration model of 1.5 degrees of freedom," Applied Mathematics and Computation, Elsevier, vol. 415(C).

    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:359:y:2019:i:c:p:433-455. 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.