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Neural Network Control-Based Drive Design of Servomotor and Its Application to Automatic Guided Vehicle

机译:基于神经网络控制的伺服电机驱动设计及其在自动导引车中的应用

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摘要

An automatic guided vehicle (AGV) is extensively used for productions in a flexible manufacture system with high efficiency and high flexibility. A servomotor-based AGV is designed and implemented in this paper. In order to steer the AGV to go along a predefined path with corner or arc, the conventional proportional-integral-derivative (PID) control is used in the system. However, it is difficult to tune PID gains at various conditions. As a result, the neural network (NN) control is considered to assist the PID control for gain tuning. The experimental results are first provided to verify the correctness of the neural network plus PID control for 400W-motor control system. Secondly, the AGV includes two sets of the designed motor systems and CAN BUS transmission so that it can move along the straight line and curve paths shown in the taped videos.
机译:自动导引车(AGV)被广泛用于具有高效率和高灵活性的柔性制造系统中的生产。本文设计并实现了基于伺服电机的AGV。为了使AGV转向带有拐角或弧形的预定路径,系统中使用了常规的比例积分微分(PID)控制。但是,很难在各种条件下调整PID增益。结果,神经网络(NN)控制被认为有助于PID控制进行增益调整。首先提供实验结果,以验证神经网络和400W电机控制系统的PID控制的正确性。其次,AGV包括两组设计的电机系统和CAN BUS传输,因此它可以沿着录像带中所示的直线和曲线路径运动。

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  • 来源
    《Mathematical Problems in Engineering》 |2015年第20期|612932.1-612932.9|共9页
  • 作者单位

    Southern Taiwan Univ Sci & Technol, Dept Elect Engn, Tainan 710, Taiwan;

    Southern Taiwan Univ Sci & Technol, Dept Elect Engn, Tainan 710, Taiwan;

    Southern Taiwan Univ Sci & Technol, Dept Elect Engn, Tainan 710, Taiwan;

    Southern Taiwan Univ Sci & Technol, Dept Elect Engn, Tainan 710, Taiwan;

    Etern Elect Ind Co, Tainan 717, Taiwan;

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