MPC and PSO based control methodology for path tracking of 4WS4WD vehicles

Tan, Q; Dai, P; Zhang, Z; Katupitiya, J

MPC and PSO based control methodology for path tracking of 4WS4WD vehicles

Tan, Q Dai, P

Zhang, Z Katupitiya, J

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Publication Type:: Journal Article
Citation:: Applied Sciences (Switzerland), 2018, 8 (6)
Issue Date:: 2018-06-19

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Field	Value	Language
dc.contributor.author	Tan, Q	en_US
dc.contributor.author	Dai, P https://orcid.org/0000-0003-0377-0775	en_US
dc.contributor.author	Zhang, Z	en_US
dc.contributor.author	Katupitiya, J	en_US
dc.date.issued	2018-06-19	en_US
dc.identifier.citation	Applied Sciences (Switzerland), 2018, 8 (6)	en_US
dc.identifier.uri	http://hdl.handle.net/10453/132244
dc.description.abstract	© 2018 by the authors. Four wheel steering and four wheel drive (4WS4WD) vehicles are over-actuated systems with superior performance. Considering the control problem caused by the system nonlinearity and over-actuated characteristics of the 4WS4WD vehicle, this paper presents two methods to enable a 4WS4WD vehicle to accurately follow a predefined path as well as its reference trajectories including velocity and acceleration profiles. The methodologies are based on model predictive control (MPC) and particle swarm optimization (PSO), respectively. The MPC method generates the virtual inputs in the upper controller and then allocates the actual inputs in the lower controller using sequential quadratic programming (SQP), whereas the PSO method is proposed as a fully optimization based method for comparison. Both methods achieve optimization of the steering angles and wheel forces for each of four independent wheels simultaneously in real time. Simulation results achieved by two different controllers in following the reference path with varying disturbances are presented. Discussion about two methodologies is provided based on their theoretical analysis and simulation results.	en_US
dc.relation.ispartof	Applied Sciences (Switzerland)	en_US
dc.relation.isbasedon	10.3390/app8061000	en_US
dc.rights	info:eu-repo/semantics/openAccess
dc.title	MPC and PSO based control methodology for path tracking of 4WS4WD vehicles	en_US
dc.type	Journal Article
utslib.citation.volume	6	en_US
utslib.citation.volume	8	en_US
utslib.for	0902 Automotive Engineering	en_US
utslib.for	0805 Distributed Computing	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 Mechanical and Mechatronic Engineering
utslib.copyright.status	open_access	*
pubs.issue	6	en_US
pubs.publication-status	Published	en_US
pubs.volume	8	en_US

Abstract:

© 2018 by the authors. Four wheel steering and four wheel drive (4WS4WD) vehicles are over-actuated systems with superior performance. Considering the control problem caused by the system nonlinearity and over-actuated characteristics of the 4WS4WD vehicle, this paper presents two methods to enable a 4WS4WD vehicle to accurately follow a predefined path as well as its reference trajectories including velocity and acceleration profiles. The methodologies are based on model predictive control (MPC) and particle swarm optimization (PSO), respectively. The MPC method generates the virtual inputs in the upper controller and then allocates the actual inputs in the lower controller using sequential quadratic programming (SQP), whereas the PSO method is proposed as a fully optimization based method for comparison. Both methods achieve optimization of the steering angles and wheel forces for each of four independent wheels simultaneously in real time. Simulation results achieved by two different controllers in following the reference path with varying disturbances are presented. Discussion about two methodologies is provided based on their theoretical analysis and simulation results.

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http://hdl.handle.net/10453/132244