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Mathematical Problems in Engineering
Volume 2015, Article ID 612932, 9 pages
Research Article

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

1Department of Electrical Engineering, Southern Taiwan University of Science and Technology, 1 Nan-Tai Street, Yung Kang District, Tainan City 710, Taiwan
2Eternity Electronic Industrial Company, Tainan City 717, Taiwan

Received 14 September 2014; Accepted 2 December 2014

Academic Editor: Mo Li

Copyright © 2015 Ming-Shyan Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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.