Neural Network Control-Based Drive Design of Servomotor and Its Application to Automatic Guided Vehicle
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 conventi...
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Series: | Mathematical Problems in Engineering |
Online Access: | http://dx.doi.org/10.1155/2015/612932 |
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doaj-7ed0bdee2fdf4cad83bf64cc48d82cce2020-11-24T23:06:27ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472015-01-01201510.1155/2015/612932612932Neural Network Control-Based Drive Design of Servomotor and Its Application to Automatic Guided VehicleMing-Shyan Wang0Seng-Chi Chen1Po-Hsiang Chuang2Shih-Yu Wu3Fu-Shung Hsu4Department of Electrical Engineering, Southern Taiwan University of Science and Technology, 1 Nan-Tai Street, Yung Kang District, Tainan City 710, TaiwanDepartment of Electrical Engineering, Southern Taiwan University of Science and Technology, 1 Nan-Tai Street, Yung Kang District, Tainan City 710, TaiwanDepartment of Electrical Engineering, Southern Taiwan University of Science and Technology, 1 Nan-Tai Street, Yung Kang District, Tainan City 710, TaiwanDepartment of Electrical Engineering, Southern Taiwan University of Science and Technology, 1 Nan-Tai Street, Yung Kang District, Tainan City 710, TaiwanEternity Electronic Industrial Company, Tainan City 717, TaiwanAn 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.http://dx.doi.org/10.1155/2015/612932 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Ming-Shyan Wang Seng-Chi Chen Po-Hsiang Chuang Shih-Yu Wu Fu-Shung Hsu |
spellingShingle |
Ming-Shyan Wang Seng-Chi Chen Po-Hsiang Chuang Shih-Yu Wu Fu-Shung Hsu Neural Network Control-Based Drive Design of Servomotor and Its Application to Automatic Guided Vehicle Mathematical Problems in Engineering |
author_facet |
Ming-Shyan Wang Seng-Chi Chen Po-Hsiang Chuang Shih-Yu Wu Fu-Shung Hsu |
author_sort |
Ming-Shyan Wang |
title |
Neural Network Control-Based Drive Design of Servomotor and Its Application to Automatic Guided Vehicle |
title_short |
Neural Network Control-Based Drive Design of Servomotor and Its Application to Automatic Guided Vehicle |
title_full |
Neural Network Control-Based Drive Design of Servomotor and Its Application to Automatic Guided Vehicle |
title_fullStr |
Neural Network Control-Based Drive Design of Servomotor and Its Application to Automatic Guided Vehicle |
title_full_unstemmed |
Neural Network Control-Based Drive Design of Servomotor and Its Application to Automatic Guided Vehicle |
title_sort |
neural network control-based drive design of servomotor and its application to automatic guided vehicle |
publisher |
Hindawi Limited |
series |
Mathematical Problems in Engineering |
issn |
1024-123X 1563-5147 |
publishDate |
2015-01-01 |
description |
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. |
url |
http://dx.doi.org/10.1155/2015/612932 |
work_keys_str_mv |
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