Intelligent coordination steering control of automated guided vehicle

Zhan, YD; Guo, YG; Zhu, JG

Intelligent coordination steering control of automated guided vehicle

Zhan, YD Guo, YG

Zhu, JG

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Publication Type:: Conference Proceeding
Citation:: 2011 International Conference on Applied Superconductivity and Electromagnetic Devices, ASEMD 2011, 2011, pp. 204 - 207
Issue Date:: 2011-12-01

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Field	Value	Language
dc.contributor.author	Zhan, YD	en_US
dc.contributor.author	Guo, YG https://orcid.org/0000-0001-6182-0684	en_US
dc.contributor.author	Zhu, JG https://orcid.org/0000-0002-9763-4047	en_US
dc.date.issued	2011-12-01	en_US
dc.identifier.citation	2011 International Conference on Applied Superconductivity and Electromagnetic Devices, ASEMD 2011, 2011, pp. 204 - 207	en_US
dc.identifier.isbn	9781424478521	en_US
dc.identifier.uri	http://hdl.handle.net/10453/19134
dc.description.abstract	In this paper, based on the neural network, fuzzy control and bang-bang control, an intelligent coordination control strategy for automated guided vehicle (AGV) steering system is presented. The dynamic steering model of distance error and orientation angle error for AGV is expressed. With least square method of system identification, the model of AGV is identified. Because a toy type of AGV is employed, its structure is simple, but AGV model parameters are variable according to the operating conditions and environment. In order to improve the dynamic performances of AGV, the intelligent coordinated control strategy is used to design the AGV controller in the AGV steering control system. Simulation and experimental results show the effectiveness of the proposed control strategy. © 2011 IEEE.	en_US
dc.relation.ispartof	2011 International Conference on Applied Superconductivity and Electromagnetic Devices, ASEMD 2011	en_US
dc.relation.isbasedon	10.1109/ASEMD.2011.6145101	en_US
dc.title	Intelligent coordination steering control of automated guided vehicle	en_US
dc.type	Conference Proceeding
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
dc.location.activity	Sydney, Australia	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CCET - Centre for Clean Energy Technology
utslib.copyright.status	open_access
pubs.publication-status	Published	en_US

Abstract:

In this paper, based on the neural network, fuzzy control and bang-bang control, an intelligent coordination control strategy for automated guided vehicle (AGV) steering system is presented. The dynamic steering model of distance error and orientation angle error for AGV is expressed. With least square method of system identification, the model of AGV is identified. Because a toy type of AGV is employed, its structure is simple, but AGV model parameters are variable according to the operating conditions and environment. In order to improve the dynamic performances of AGV, the intelligent coordinated control strategy is used to design the AGV controller in the AGV steering control system. Simulation and experimental results show the effectiveness of the proposed control strategy. © 2011 IEEE.

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http://hdl.handle.net/10453/19134