IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v196y2025ics0960077925004205.html
   My bibliography  Save this article

Adaptive neural finite-time tracking control based on modified command-filtered backstepping method for MIMO nonlinear systems

Author

Listed:
  • Zhao, Xu
  • Gao, Yang
  • Huang, Haisong
  • Fan, Qingsong
  • Chen, Jiajia
  • Deveci, Muhammet
  • Ding, Weiping

Abstract

This paper develops an adaptive neural finite-time tracking control scheme based on modified command-filtered backstepping control method (MCFBC) for multi-input and multi-output (MIMO) nonlinear systems. Firstly, by introducing some constant matrices, command-filtered backstepping control method (CFBC) is modified. Compared with CFBC, MCFBC ensures that virtual control signals are linearized, which lowers the complexity of the controller such that the control performance is elevated. Secondly, different from CFBC, MCFBC does not directly use the spectral boundedness of control directions in stability proof any more. Thirdly, lumped uncertainties are approximated by neural network (NN) and a more generalized inequality is proposed to surmount the technical difficulties of finite-time stability analysis. Fourthly, the singularity problem is circumvented. Command filters are introduced to remove the repeated differentiation of pseudocontrol signals. An error compensation system is constructed to lower the adverse effect from filter errors. This proposed controller guarantees that all signals in the closed-loop system converge to a bounded region within finite time and the system output can follow the given signal with a considerably small tracking error. Finally, flexible joint manipulations are used to validate this control scheme.

Suggested Citation

  • Zhao, Xu & Gao, Yang & Huang, Haisong & Fan, Qingsong & Chen, Jiajia & Deveci, Muhammet & Ding, Weiping, 2025. "Adaptive neural finite-time tracking control based on modified command-filtered backstepping method for MIMO nonlinear systems," Chaos, Solitons & Fractals, Elsevier, vol. 196(C).
    • Handle: RePEc:eee:chsofr:v:196:y:2025:i:c:s0960077925004205
    DOI: 10.1016/j.chaos.2025.116407
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077925004205
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.chaos.2025.116407?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. Zhao, Yuzhuo & Ma, Dan, 2025. "Time-delay neural network observer-based adaptive finite-time prescribed performance control for nonlinear systems with unknown time-delay," Chaos, Solitons & Fractals, Elsevier, vol. 191(C).
    2. Xu, Ke & Wang, Huanqing & Liu, Peter Xiaoping, 2023. "Adaptive fuzzy finite-time tracking control of nonlinear systems with unmodeled dynamics," Applied Mathematics and Computation, Elsevier, vol. 450(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. Sui, Shuai & Yu, Yuelei & Tong, Shaocheng & Philip Chen, C.L., 2024. "Event-triggered robust fuzzy adaptive control for non-strict feedback nonlinear system with prescribed performance," Applied Mathematics and Computation, Elsevier, vol. 474(C).
    2. Liu, Yanli & Hao, Li-Ying, 2024. "Adaptive tracking control for constrained nonlinear nonstrict-feedback switched stochastic systems with unknown control directions," Applied Mathematics and Computation, Elsevier, vol. 473(C).
    3. Liu, Yongchao & Zhao, Ning, 2024. "Adaptive dynamic event-triggered asymptotic control for uncertain nonlinear systems," Chaos, Solitons & Fractals, Elsevier, vol. 189(P1).

    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:chsofr:v:196:y:2025:i:c:s0960077925004205. 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: Thayer, Thomas R. (email available below). General contact details of provider: https://www.journals.elsevier.com/chaos-solitons-and-fractals .

    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.