Current studentsExisting staffContact us
 

Drag coefficient estimation model to simulate dynamic control of autonomous underwater vehicle (AUV) motion

Simple item page
dc.contributor.authorTan, K.
dc.contributor.authorLu, T.
dc.contributor.authorAnvar, A.
dc.contributor.conferenceInternational Congress on Modelling and Simulation (20th : 2013 : Adelaide, South Australia)
dc.contributor.editorPiantadosi, J.
dc.contributor.editorAnderssen, R.S.
dc.contributor.editorBoland, J.
dc.date.issued2013
dc.description22nd National Conference of the Australian Society for Operations Research — ASOR 2013 DSTO led Defence Operations Research Symposium — DORS 2013
dc.description.abstractA vehicle dynamics model is crucial for the design of control system for an autonomous underwater vehicle (AUV). However, it is not a simple task to determine the hydrodynamic forces especially the drag coefficient involved for any particular vehicle model. This paper describes a novel approach to approximate the drag coefficient of any given vehicle shapes and sizes using fourth order regression method. The vehicle is subjected to pre-conditioning phase, where it can be done with CFD modelling or subject to simple experimental test within an open environment. In the pre-conditioning phase, the vehicle is required to navigate freely around custom test environment to obtain the drag profile in real-time. With sufficient data, using the correlation 3D graph of drag coefficient and the change in angles, the drag profile of any given shape can be determined. The accuracy of the model is based on the frequency of trial runs, as well as the efficiency of the vehicle’s on-board inertial navigation sensors. In this paper, the proposed approach is being demonstrated using ANSYS-CFX and the results obtained provide close approximation to the real drag coefficient. Therefore, the proposed novel approach is promising and can be used to find the drag coefficients for any given underwater vehicle at any conditions.
dc.description.statementofresponsibilityKuan M.Tan, Tien-Fu Lu, Amir Anvar
dc.description.urihttp://www.mssanz.org.au/modsim2013/index.html
dc.identifier.citationMODSIM2013: 20th International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand, December 2013 / J. Piantadosi, R. S. Anderssen and J. Boland (eds.): pp.963-969.
dc.identifier.isbn9780987214331
dc.identifier.orcidLu, T. [0000-0001-9757-9028]
dc.identifier.urihttp://hdl.handle.net/2440/82448
dc.language.isoen
dc.publisherThe Modelling and Simulation Society of Aust & NZ
dc.publisher.placeAustralia
dc.rightsCopyright status unknown
dc.source.urihttp://www.mssanz.org.au/modsim2013/C10/tan.pdf
dc.subjectAutonomous Underwater Vehicle
dc.subjectRobotics
dc.subjectHydrodynamics
dc.subjectCFD
dc.subjectSystem Identification
dc.subjectModeling
dc.subjectSimulation
dc.subjectControl
dc.subjectDrag
dc.titleDrag coefficient estimation model to simulate dynamic control of autonomous underwater vehicle (AUV) motion
dc.typeConference paper
pubs.publication-statusPublished

Files

Collections

Mechanical Engineering conference papers