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

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  • Ming-Shyan Wang
  • Seng-Chi Chen
  • Po-Hsiang Chuang
  • Shih-Yu Wu
  • Fu-Shung Hsu

Abstract

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 400 W-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.

Suggested Citation

  • Ming-Shyan Wang & Seng-Chi Chen & Po-Hsiang Chuang & Shih-Yu Wu & Fu-Shung Hsu, 2015. "Neural Network Control-Based Drive Design of Servomotor and Its Application to Automatic Guided Vehicle," Mathematical Problems in Engineering, Hindawi, vol. 2015, pages 1-9, October.
    • Handle: RePEc:hin:jnlmpe:612932
    DOI: 10.1155/2015/612932
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