Optimal path-following control of a smart powered wheelchair.

Nguyen, N; Nguyen, HT; Su, S

Optimal path-following control of a smart powered wheelchair.

Nguyen, N

Nguyen, HT

Su, S

Permalink

Publication Type:: Conference Proceeding
Citation:: Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference, 2008, pp. 5025 - 5028
Issue Date:: 2008-12-01

Open Access

Copyright Clearance Process

Recently Added
In Progress
Open Access

This item is open access.

Adobe PDF

Download full textAdobe PDF (216.27 kB)

View statistics

Full metadata record

Field	Value	Language
dc.contributor.author	Nguyen, N https://orcid.org/0000-0002-9958-9876	en_US
dc.contributor.author	Nguyen, HT https://orcid.org/0000-0003-3373-8178	en_US
dc.contributor.author	Su, S https://orcid.org/0000-0002-5720-8852	en_US
dc.date.issued	2008-12-01	en_US
dc.identifier.citation	Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference, 2008, pp. 5025 - 5028	en_US
dc.identifier.issn	1557-170X	en_US
dc.identifier.uri	http://hdl.handle.net/10453/11945
dc.description.abstract	This paper proposes an optimal path-following control approach for a smart powered wheelchair. Lyapunov's second method is employed to find a stable position tracking control rule. To guarantee robust performance of this wheelchair system even under model uncertainties, an advanced robust tracking is utilised based on the combination of a systematic decoupling technique and a neural network design. A calibration procedure is adopted for the wheelchair system to improve positioning accuracy. After the calibration, the accuracy is improved significantly. Two real-time experimental results obtained from square tracking and door passing tasks confirm the performance of proposed approach.	en_US
dc.relation	http://purl.org/au-research/grants/arc/DP0666942
dc.relation	http://purl.org/au-research/grants/arc/LE0668541
dc.relation.ispartof	Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference	en_US
dc.subject.mesh	Wheelchairs	en_US
dc.subject.mesh	Robotics	en_US
dc.subject.mesh	Algorithms	en_US
dc.subject.mesh	Computing Methodologies	en_US
dc.subject.mesh	Artificial Intelligence	en_US
dc.subject.mesh	Pattern Recognition, Automated	en_US
dc.title	Optimal path-following control of a smart powered wheelchair.	en_US
dc.type	Conference Proceeding
utslib.for	0903 Biomedical Engineering	en_US
dc.location.activity	Vancouver, Canada	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/Strength - CHT - Health Technologies
utslib.copyright.status	open_access
pubs.publication-status	Published	en_US

Abstract:

This paper proposes an optimal path-following control approach for a smart powered wheelchair. Lyapunov's second method is employed to find a stable position tracking control rule. To guarantee robust performance of this wheelchair system even under model uncertainties, an advanced robust tracking is utilised based on the combination of a systematic decoupling technique and a neural network design. A calibration procedure is adopted for the wheelchair system to improve positioning accuracy. After the calibration, the accuracy is improved significantly. Two real-time experimental results obtained from square tracking and door passing tasks confirm the performance of proposed approach.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/11945