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A MRAC Principle for a Single-Link Electrically Driven Robot with Parameter Uncertainties

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  • Carlos Aguilar-Avelar
  • Javier Moreno-Valenzuela

Abstract

In this paper, a model reference adaptive control (MRAC) principle for a one-degree-of-freedom rigid-link electrically driven robot is presented. The proposed control methodology addresses the problem of trajectory tracking with parameter uncertainties in the dynamic model of the system and proposes adaptation laws for the electrical and mechanical parameters. Closed-loop stability is rigorously discussed, proving that the tracking error trajectories converge to the origin exponentially. With the aim of performing experimental comparisons, two control schemes are also revisited theoretically and experimentally: one is an algorithm previously reported in the literature and the other is an adaptive controller derived under the assumption that the electrical dynamics of the actuator are negligible. All the discussed controllers have been implemented in an experimental setup consisting in a rigid-link robot actuated with brushed DC motor. The comparison indicates that better results are obtained with the new MRAC scheme.

Suggested Citation

  • 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.
  • Handle: RePEc:hin:complx:9296012
    DOI: 10.1155/2017/9296012
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    References listed on IDEAS

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    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.
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    Cited by:

    1. José Rafael García-Sánchez & Ramón Silva-Ortigoza & Salvador Tavera-Mosqueda & Celso Márquez-Sánchez & Victor Manuel Hernández-Guzmán & Mayra Antonio-Cruz & Gilberto Silva-Ortigoza & Hind Taud, 2017. "Tracking Control for Mobile Robots Considering the Dynamics of All Their Subsystems: Experimental Implementation," Complexity, Hindawi, vol. 2017, pages 1-18, December.

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