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Repetitive control of electrically driven robot manipulators

Author

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  • Mohammad Fateh
  • Hojjat Tehrani
  • Seyed Karbassi

Abstract

This article presents a novel robust discrete repetitive control of electrically driven robot manipulators for tracking of a periodic trajectory. We propose a novel model, which presents the highly non-linear dynamics of robot manipulator in the form of linear discrete-time time-varying system. Based on the proposed model, we develop a two-term control law. The first term is an ordinary time-optimal and minimum-norm (TOMN) control by employing parametric controllers to guarantee stability. The second term is a novel robust control to improve the control performance in the face of uncertainties. The robust control estimates and compensates uncertainties including the parametric uncertainty, unmodelled dynamics and external disturbances. Performance of the proposed method is compared with two discrete methods, namely the TOMN control and an adaptive iterative learning (AIL) control. Simulation results confirm superiority of the proposed method in terms of the convergence speed and precision.

Suggested Citation

  • 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.
    • Handle: RePEc:taf:tsysxx:v:44:y:2013:i:4:p:775-785
    DOI: 10.1080/00207721.2011.625478
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    Cited by:

    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.

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