Publication: Application of Automatic Differentiation to Race Car Performance Optimisation
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Application of Automatic Differentiation to Race Car Performance Optimisation

- incollection -
 

Author(s)
Daniele Casanova , Robin S. Sharp , Mark Final , Bruce Christianson , Pat Symonds

Published in
Automatic Differentiation of Algorithms: From Simulation to Optimization

Editor(s)
George Corliss, Christèle Faure, Andreas Griewank, Laurent Hascoët, Uwe Naumann

Year
2002

Publisher
Springer

Abstract
A 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 non-linear programming problem is solved using the sequential quadratic programming algorithm SNOPT for constrained optimisation. The automatic differentiation software tool adopt is 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.

Cross-References
Corliss2002ADo

BibTeX
@INCOLLECTION{
         Casanova2002AoA,
       author = "Daniele Casanova and Robin S. Sharp and Mark Final and Bruce Christianson and Pat
         Symonds",
       title = "Application of Automatic Differentiation to Race Car Performance Optimisation",
       pages = "117--124",
       chapter = "12",
       crossref = "Corliss2002ADo",
       booktitle = "Automatic Differentiation of Algorithms: From Simulation to Optimization",
       year = "2002",
       editor = "George Corliss and Christ{\`e}le Faure and Andreas Griewank and Laurent
         Hasco{\"e}t and Uwe Naumann",
       series = "Computer and Information Science",
       publisher = "Springer",
       address = "New York, NY",
       abstract = "A 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 non-linear programming problem is solved using the sequential
         quadratic programming algorithm SNOPT for constrained optimisation. The automatic differentiation
         software tool \textbf{AD}\raisebox{-.25ex}{\textsl{opt}} is 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.",
       referred = "[Caillau2002OCS]."
}


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