Johan Åkesson
Lund University, Department of Automatic Control, Lund/Modelon AB, Lund, Sweden
Willi Braun
University of Applied Sciences Bielefeld, Bielefeld, Germany
Petter Lindholm
Lund University, Department of Mathematics, Lund, Sweden
Bernhard Bachmann
University of Applied Sciences Bielefeld, Bielefeld, Germany
Ladda ner artikel
http://dx.doi.org/10.3384/ecp12076185Ingår i: Proceedings of the 9th International MODELICA Conference; September 3-5; 2012; Munich; Germany
Linköping Electronic Conference Proceedings 76:18, s. 185-196
Publicerad: 2012-11-19
ISBN: 978-91-7519-826-2
ISSN: 1650-3686 (tryckt), 1650-3740 (online)
Derivatives; or Jacobians; are commonly required by numerical algorithms. Access to accurate Jacobians often improves the performance and robustness of algorithms; and in addition; efficient implementation of Jacobian computations can reduce the overall execution time. In this paper; we present methods for computing Jacobians in the context of the Functional Mock-up Interface (FMI); and Modelica. Two prototype implementations; in Jmodelica.org and OpenModelica are presented and compared in industrial benchmarks.
Functional Mock-up Interface; Analytic Jacobians; Automatic Differentiation; JModelica.org; OpenModelica
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