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To investigate the motion of a ship in the ocean, a six-degree-of-freedom hydraulically driven parallel mechanism is designed, the inverse solution algorithm of parallel robot is derived, and the control algorithm of parallel robot is established. The control performance of the parallel robot is developed and improved through co-simulation employing mechanical, hydraulic, and control software. PID control, Fuzzy PID control, and Fuzzy BPNN (Backpropagation Neural Network) PID control are developed for the parallel mechanism with multiple inputs and outputs, high nonlinearity, and strong coupling. The results indicate that the displacement error of the parallel platform have good tracking performance when under Fuzzy BPNN PID control.

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Fuzzy Backpropagation Neural Network PID Control of a 6-DOF Parallel Robot

  • 会议论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年

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  • Liugang Chen,
  • Pengcheng Zhu,
  • Wang Qiang,
  • Xingbin Zhang,
  • Shufen Wang

摘要

To investigate the motion of a ship in the ocean, a six-degree-of-freedom hydraulically driven parallel mechanism is designed, the inverse solution algorithm of parallel robot is derived, and the control algorithm of parallel robot is established. The control performance of the parallel robot is developed and improved through co-simulation employing mechanical, hydraulic, and control software. PID control, Fuzzy PID control, and Fuzzy BPNN (Backpropagation Neural Network) PID control are developed for the parallel mechanism with multiple inputs and outputs, high nonlinearity, and strong coupling. The results indicate that the displacement error of the parallel platform have good tracking performance when under Fuzzy BPNN PID control.