IDEAS home Printed from https://ideas.repec.org/a/taf/tsysxx/v46y2015i5p808-817.html
   My bibliography  Save this article

Design of a robust output-feedback-based modified repetitive-control system

Author

Listed:
  • Lan Zhou
  • Jinhua She

Abstract

This paper concerns the problem of designing a robust output-feedback-based modified repetitive-control system for a class of strictly proper plants with periodic uncertainties. Exploiting the periodicity of repetitive control, a continuous-discrete two-dimensional (2D) model is built so that the control and learning actions can be adjusted preferentially by means of the control gains. The combination of the singular-value decomposition of the output matrix and the Lyapunov stability theory is used to derive a linear-matrix-inequality-(LMI-) based asymptotic stability condition. Two tuning parameters in the LMI regulate the choice of the parameters in the 2D control law and thereby enable the preferential adjustment of control and learning. A numerical example illustrates the tuning procedure and demonstrates the validity of the method.

Suggested Citation

  • 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.
    • Handle: RePEc:taf:tsysxx:v:46:y:2015:i:5:p:808-817
    DOI: 10.1080/00207721.2013.791002
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00207721.2013.791002
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/00207721.2013.791002?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. Mohammad Fateh & Hojjat Tehrani & Seyed Karbassi, 2013. "Repetitive control of electrically driven robot manipulators," International Journal of Systems Science, Taylor & Francis Journals, vol. 44(4), pages 775-785.
    2. Xiao-Dong Li & Tommy Chow & L.L. Cheng, 2013. "Adaptive iterative learning control of non-linear MIMO continuous systems with iteration-varying initial error and reference trajectory," International Journal of Systems Science, Taylor & Francis Journals, vol. 44(4), pages 786-794.
    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. 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.
    2. 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).

    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. Ahsene Boubakir & Salim Labiod & Fares Boudjema & Franck Plestan, 2014. "Linear adaptive control of a class of SISO nonaffine nonlinear systems," International Journal of Systems Science, Taylor & Francis Journals, vol. 45(12), pages 2490-2498, December.
    2. Lan Zhou & Jinhua She & Min Wu, 2015. "A one-step method of designing an observer-based modified repetitive-control system," International Journal of Systems Science, Taylor & Francis Journals, vol. 46(14), pages 2617-2627, October.
    3. Lin Xiao & Yunong Zhang, 2016. "Dynamic design, numerical solution and effective verification of acceleration-level obstacle-avoidance scheme for robot manipulators," International Journal of Systems Science, Taylor & Francis Journals, vol. 47(4), pages 932-945, March.
    4. Pedro V. S. G. de Lima & Rafael C. Neto & Francisco A. S. Neves & Fabrício Bradaschia & Helber E. P. de Souza & Eduardo J. Barbosa, 2023. "Zero-Phase FIR Filter Design Algorithm for Repetitive Controllers," Energies, MDPI, vol. 16(5), pages 1-33, March.
    5. Chen, Dongjie & Xu, Ying & Lu, Tiantian & Li, Guojun, 2024. "Multi-phase iterative learning control for high-order systems with arbitrary initial shifts," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 216(C), pages 231-245.
    6. Carlos Aguilar-Avelar & Javier Moreno-Valenzuela, 2017. "A MRAC Principle for a Single-Link Electrically Driven Robot with Parameter Uncertainties," Complexity, Hindawi, vol. 2017, pages 1-13, January.

    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:taf:tsysxx:v:46:y:2015:i:5:p:808-817. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/TSYS20 .

    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.