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Model Reference Adaptive Control and Fuzzy Neural Network Synchronous Motion Compensator for Gantry Robots

Author

Listed:
  • Chin-Sheng Chen

    (Graduate Institute of Automation Technology, National Taipei University of Technology, Taipei 10608, Taiwan)

  • Nien-Tsu Hu

    (Graduate Institute of Automation Technology, National Taipei University of Technology, Taipei 10608, Taiwan)

Abstract

A model reference adaptive control and fuzzy neural network (FNN) synchronous motion compensator for a gantry robot is presented in this paper. This paper proposes the development and application of gantry robots with MRAC and FNN online compensators. First, we propose a model reference adaptive controller (MRAC) under the cascade control method to make the reference model close to the real model and reduce tracking errors for the single axis. Then, a fuzzy neural network compensator for the gantry robot is proposed to compensate for the synchronous errors between the dual servo motors to improve precise movement. In addition, an online parameter training method is proposed to adjust the parameters of the FNN. Finally, the experimental results show that the proposed method improves the synchronous errors of the gantry robot and demonstrates the methodology in this paper. This study also successfully integrates the hardware and successfully verifies the proposed methods.

Suggested Citation

  • Chin-Sheng Chen & Nien-Tsu Hu, 2021. "Model Reference Adaptive Control and Fuzzy Neural Network Synchronous Motion Compensator for Gantry Robots," Energies, MDPI, vol. 15(1), pages 1-17, December.
    • Handle: RePEc:gam:jeners:v:15:y:2021:i:1:p:123-:d:710749
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