IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v256y2015icp514-528.html
   My bibliography  Save this article

Adaptive fuzzy tracking control for stochastic nonlinear systems with unknown time-varying delays

Author

Listed:
  • Li, Junmin
  • Yue, Hongyun

Abstract

This paper addresses the problem of adaptive tracking control for a class of stochastic strict-feedback nonlinear time-varying delays systems using fuzzy logic systems (FLS). In this paper, quadratic functions are used as Lyapunov functions to analyze the stability of systems, other than the fourth moment approach proposed by H. Deng and M. Krstic, and the hyperbolic tangent functions are introduced to deal with the Hessian terms. This approach overcomes the drawback of the traditional quadratic moment approach and reduce the complexity of design procedure and controller. Based on the backstepping technique, the appropriate Lyapunov–Krasovskii functionals and the FLS, the adaptive fuzzy controller is well designed. The proposed adaptive fuzzy controller guarantees that all the signals in the closed-loop system are bounded in probability and the tracking error can converge to a small residual set around the origin in the mean square sense.

Suggested Citation

  • Li, Junmin & Yue, Hongyun, 2015. "Adaptive fuzzy tracking control for stochastic nonlinear systems with unknown time-varying delays," Applied Mathematics and Computation, Elsevier, vol. 256(C), pages 514-528.
  • Handle: RePEc:eee:apmaco:v:256:y:2015:i:c:p:514-528
    DOI: 10.1016/j.amc.2014.12.104
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0096300314017652
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.amc.2014.12.104?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.

    Citations

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


    Cited by:

    1. Liu, Yanli & Wang, Runzhi & Hao, Li-Ying, 2022. "Adaptive TD control of full-state-constrained nonlinear stochastic switched systems," Applied Mathematics and Computation, Elsevier, vol. 427(C).
    2. Xin, Li-Ping & Yu, Bo & Zhao, Lin & Yu, Jinpeng, 2020. "Adaptive fuzzy backstepping control for a two continuous stirred tank reactors process based on dynamic surface control approach," Applied Mathematics and Computation, Elsevier, vol. 377(C).
    3. Xi, Changjiang & Dong, Jiuxiang, 2019. "Adaptive fuzzy guaranteed performance control for uncertain nonlinear systems with event-triggered input," Applied Mathematics and Computation, Elsevier, vol. 363(C), pages 1-1.
    4. Min, Huifang & Xu, Shengyuan & Yu, Xin & Fei, Shumin & Cui, Guozeng, 2020. "Adaptive Tracking Control for Stochastic Nonlinear Systems with Full-State Constraints and Unknown Covariance Noise," Applied Mathematics and Computation, Elsevier, vol. 385(C).
    5. Zhai, Ding & Lu, An-Yang & Dong, Jiuxiang & Zhang, Qing-Ling, 2017. "Stability analysis and state feedback control of continuous-time T–S fuzzy systems via anew switched fuzzy Lyapunov function approach," Applied Mathematics and Computation, Elsevier, vol. 293(C), pages 586-599.
    6. Heng Liu & Ye Chen & Guanjun Li & Wei Xiang & Guangkui Xu, 2017. "Adaptive Fuzzy Synchronization of Fractional-Order Chaotic (Hyperchaotic) Systems with Input Saturation and Unknown Parameters," Complexity, Hindawi, vol. 2017, pages 1-16, November.
    7. Wang, Yingchun & Zhang, Jiaxin & Zhang, Huaguang & Xie, Xiangpeng, 2021. "Finite-time adaptive neural control for nonstrict-feedback stochastic nonlinear systems with input delay and output constraints," Applied Mathematics and Computation, Elsevier, vol. 393(C).
    8. Xiao, Wenbin & Cao, Liang & Dong, Guowei & Zhou, Qi, 2019. "Adaptive fuzzy control for pure-feedback systems with full state constraints and unknown nonlinear dead zone," Applied Mathematics and Computation, Elsevier, vol. 343(C), pages 354-371.
    9. Dong, Jiuxiang & Hou, Junteng, 2017. "Output feedback fault-tolerant control by a set-theoretic description of T–S fuzzy systems," Applied Mathematics and Computation, Elsevier, vol. 301(C), pages 117-134.

    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:256:y:2015:i:c:p:514-528. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.