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dc.contributor.authorChristianson, B.
dc.contributor.authorCasanova, D.
dc.contributor.authorSharp, R.S.
dc.contributor.authorFinal, M.
dc.contributor.authorSymonds, P.
dc.contributor.editorCorliss, G.
dc.contributor.editorFaure, C.
dc.contributor.editorGriewank, A.
dc.contributor.editorNaumann, U.
dc.identifier.citationChristianson , B , Casanova , D , Sharp , R S , Final , M & Symonds , P 2002 , Application of automatic differentiation to race car performance optimisation . in G Corliss , C Faure , A Griewank & U Naumann (eds) , Automatic Differentiation of Algorithms : From Simulation to Optimization . Springer , pp. 117-124 .
dc.identifier.otherPURE: 97785
dc.identifier.otherPURE UUID: eff696bb-28aa-454a-9a80-e4749ac977d2
dc.identifier.otherdspace: 2299/4351
dc.descriptionCopyright Springer. [Full text of this chapter is not available in the UHRA]
dc.description.abstractA formal method for the evaluation of the minimum time vehicle manoeuvre is described. The problem is treated as one of optimal control and is solved using a direct transcription method. The resulting nonlinear programming problem is solved using the sequential quadratic programming algorithm SNOPT for constrained optimisation. The automatic differentiation software too ADoptis used for the evaluation of the first-order derivatives of objective and constraint functions with respect to the control variables. The implementation of automatic differentiation is more robust and ten times as fast compared to the use of a finite difference determination of the Jacobian.en
dc.relation.ispartofAutomatic Differentiation of Algorithms
dc.titleApplication of automatic differentiation to race car performance optimisationen
dc.contributor.institutionSchool of Computer Science
dc.contributor.institutionCentre for Computer Science and Informatics Research
dc.contributor.institutionScience & Technology Research Institute

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