Model predictive control of gantry crane with input nonlinearity compensation

Su, SW; Nguyen, H; Jarman, R; Zhu, J; Lowe, D; McLean, P; Huang, S; Nguyen, NT; Nicholson, R; Weng, K

Model predictive control of gantry crane with input nonlinearity compensation

Su, SW

Nguyen, H

Jarman, R Zhu, J

Lowe, D McLean, P

Huang, S

Nguyen, NT

Nicholson, R Weng, K

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Publication Type:: Conference Proceeding
Citation:: World Academy of Science, Engineering and Technology, 2009, 38 pp. 312 - 316
Issue Date:: 2009-02-01

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Field	Value	Language
dc.contributor.author	Su, SW https://orcid.org/0000-0002-5720-8852	en_US
dc.contributor.author	Nguyen, H https://orcid.org/0000-0003-3373-8178	en_US
dc.contributor.author	Jarman, R	en_US
dc.contributor.author	Zhu, J https://orcid.org/0000-0002-9763-4047	en_US
dc.contributor.author	Lowe, D	en_US
dc.contributor.author	McLean, P https://orcid.org/0000-0002-7731-4927	en_US
dc.contributor.author	Huang, S https://orcid.org/0000-0002-6124-4178	en_US
dc.contributor.author	Nguyen, NT https://orcid.org/0000-0002-9958-9876	en_US
dc.contributor.author	Nicholson, R	en_US
dc.contributor.author	Weng, K	en_US
dc.date.issued	2009-02-01	en_US
dc.identifier.citation	World Academy of Science, Engineering and Technology, 2009, 38 pp. 312 - 316	en_US
dc.identifier.issn	2010-376X	en_US
dc.identifier.uri	http://hdl.handle.net/10453/11136
dc.description.abstract	This paper proposed a nonlinear model predictive control (MPC) method for the control of gantry crane. One of the main motivations to apply MPC to control gantry crane is based on its ability to handle control constraints for multivariable systems. A pre-compensator is constructed to compensate the input nonlinearity (nonsymmetric dead zone with saturation) by using its inverse function. By well tuning the weighting function matrices, the control system can properly compromise the control between crane position and swing angle. The proposed control algorithm was implemented for the control of gantry crane system in System Control Lab of University of Technology, Sydney (UTS), and achieved desired experimental results. © 2009 WASET.ORG.	en_US
dc.relation.ispartof	World Academy of Science, Engineering and Technology	en_US
dc.title	Model predictive control of gantry crane with input nonlinearity compensation	en_US
dc.type	Conference Proceeding
utslib.citation.volume	38	en_US
utslib.for	0910 Manufacturing Engineering	en_US
dc.location.activity	Penang, Malaysia	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 Biomedical Engineering
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/Faculty of Engineering and Information Technology/School of Mechanical and Mechatronic Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CAS - Centre for Autonomous Systems
pubs.organisational-group	/University of Technology Sydney/Strength - CCET - Centre for Clean Energy Technology
pubs.organisational-group	/University of Technology Sydney/Strength - CHT - Health Technologies
utslib.copyright.status	open_access
pubs.publication-status	Published	en_US
pubs.volume	38	en_US

Abstract:

This paper proposed a nonlinear model predictive control (MPC) method for the control of gantry crane. One of the main motivations to apply MPC to control gantry crane is based on its ability to handle control constraints for multivariable systems. A pre-compensator is constructed to compensate the input nonlinearity (nonsymmetric dead zone with saturation) by using its inverse function. By well tuning the weighting function matrices, the control system can properly compromise the control between crane position and swing angle. The proposed control algorithm was implemented for the control of gantry crane system in System Control Lab of University of Technology, Sydney (UTS), and achieved desired experimental results. © 2009 WASET.ORG.

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http://hdl.handle.net/10453/11136