IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v11y2023i19p4033-d1245790.html
   My bibliography  Save this article

Nonlinear Functional Observer Design for Robot Manipulators

Author

Listed:
  • Hoang Vu Dao

    (Graduate School of Mechanical Engineering, University of Ulsan, Ulsan 44610, Republic of Korea)

  • Manh Hung Nguyen

    (Graduate School of Mechanical Engineering, University of Ulsan, Ulsan 44610, Republic of Korea)

  • Kyoung Kwan Ahn

    (School of Mechanical Engineering, University of Ulsan, Ulsan 44610, Republic of Korea)

Abstract

In this paper, a nonlinear functional observer (NFO) is first proposed for the control design of robot manipulators under model uncertainties, external disturbances, and a lack of joint velocity information. In principle, the proposed NFO can estimate not only lumped disturbances and uncertainties but also unmeasurable joint velocities, which are then fed back into the main controller. Compared to the well-known ESO design, the proposed NFO has a simpler structure, more accurate estimations, and less computational effort, and consequently, it is easier for practical implementation. Moreover, unnecessary observations of joint displacements are avoided when compared to the well-known extended state observer (ESO). Based on the Lyapunov theory, globally uniformly ultimately bounded estimation performance is guaranteed by the proposed NFO. Consequently, it is theoretically proven that the estimation performances of the NFO are better than those of the ESO. Simulations with a two-degree-of-freedom (2-DOF) robot manipulator are conducted to verify the effectiveness of the proposed algorithm in terms of not only the estimation performance but also the closed-loop control performance.

Suggested Citation

  • Hoang Vu Dao & Manh Hung Nguyen & Kyoung Kwan Ahn, 2023. "Nonlinear Functional Observer Design for Robot Manipulators," Mathematics, MDPI, vol. 11(19), pages 1-16, September.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:19:p:4033-:d:1245790
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/11/19/4033/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/11/19/4033/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Che, Haochi & Huang, Jun & Zhao, Xudong & Ma, Xiang & Xu, Ning, 2020. "Functional interval observer for discrete-time systems with disturbances," Applied Mathematics and Computation, Elsevier, vol. 383(C).
    2. Jun Yang & Jing Na & Guanbin Gao & Chao Zhang, 2018. "Adaptive Neural Tracking Control of Robotic Manipulators with Guaranteed NN Weight Convergence," Complexity, Hindawi, vol. 2018, pages 1-11, October.
    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. Wang, Ziyun & Wang, Xianzhe & Wang, Yan, 2024. "Orthotope-search-expansion-based extended zonotopic Kalman filter design for a discrete-time linear parameter-varying system with a dual-noise term," Applied Mathematics and Computation, Elsevier, vol. 474(C).
    2. 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).
    3. Guanyu Lai & Sheng Zhou & Weijun Yang & Xiaodong Wang & Fang Wang, 2023. "Prescribed Fixed-Time Adaptive Neural Control for Manipulators with Uncertain Dynamics and Actuator Failures," Mathematics, MDPI, vol. 11(13), pages 1-20, June.
    4. Rabeh Abbassi & Houssem Jerbi & Mourad Kchaou & Theodore E. Simos & Spyridon D. Mourtas & Vasilios N. Katsikis, 2023. "Towards Higher-Order Zeroing Neural Networks for Calculating Quaternion Matrix Inverse with Application to Robotic Motion Tracking," Mathematics, MDPI, vol. 11(12), pages 1-21, June.
    5. Huang, Jun & Yang, Lin & Trinh, Hieu, 2021. "Robust control for incremental quadratic constrained nonlinear time-delay systems subject to actuator saturation," Applied Mathematics and Computation, Elsevier, vol. 405(C).
    6. Xie, Jiyang & Zhu, Shuqian & Zhang, Dawei, 2022. "A robust distributed secure interval observation approach for uncertain discrete-time positive systems under deception attacks," Applied Mathematics and Computation, Elsevier, vol. 413(C).
    7. Yun-Shan Wei & Qing-Yuan Xu, 2018. "Iterative Learning Control for Linear Discrete-Time Systems with Randomly Variable Input Trail Length," Complexity, Hindawi, vol. 2018, pages 1-6, November.
    8. Zhang, Tu & Li, Liwei & Shen, Mouquan, 2021. "Interval observer-based finite-time control for linear parameter-varying systems," Applied Mathematics and Computation, Elsevier, vol. 411(C).
    9. Hadeel Alharbi & Houssem Jerbi & Mourad Kchaou & Rabeh Abbassi & Theodore E. Simos & Spyridon D. Mourtas & Vasilios N. Katsikis, 2023. "Time-Varying Pseudoinversion Based on Full-Rank Decomposition and Zeroing Neural Networks," Mathematics, MDPI, vol. 11(3), pages 1-14, January.
    10. Houssem Jerbi & Izzat Al-Darraji & Georgios Tsaramirsis & Lotfi Ladhar & Mohamed Omri, 2023. "Hamilton–Jacobi Inequality Adaptive Robust Learning Tracking Controller of Wearable Robotic Knee System," Mathematics, MDPI, vol. 11(6), pages 1-32, March.

    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:gam:jmathe:v:11:y:2023:i:19:p:4033-:d:1245790. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.