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Advances in Automatic Differentiation pp 175–185Cite as

Adjoints for Time-Dependent Optimal Control

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Part of the book series: Lecture Notes in Computational Science and Engineering ((LNCSE,volume 64))

Summary

The use of discrete adjoints in the context of a hard time-dependent optimal control problem is considered. Gradients required for the steepest descent method are computed by code that is generated automatically by the differentiation-enabled NAGWare Fortran compiler. Single time steps are taped using an overloading approach. The entire evolution is reversed based on an efficient checkpointing schedule that is computed by revolve. The feasibility of nonlinear optimization based on discrete adjoints is supported by our numerical results.

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of Hertfordshire, UK

    Jan Riehme

  2. Department of Mathematics, Technische Universität Dresden, Germany

    Andrea Walther

  3. Department of Mechanical Engineering, Technische Universität Dresden, Germany

    Jörg Stiller

  4. Department of Computer Science, RWTH Aachen University, Germany

    Uwe Naumann

Authors
  1. Jan Riehme
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  2. Andrea Walther
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  3. Jörg Stiller
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  4. Uwe Naumann
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Editor information

Editors and Affiliations

  1. Institute for Scientific Computing, RWTH Aachen University, 52056, Aachen, Germany

    Christian H. Bischof  & H. Martin Bücker  & 

  2. Mathematics and Computer Science Division, Argonne National Laboratory, 9700 S Cass Ave, Argonne, IL, 60439, USA

    Paul Hovland  & Jean Utke  & 

  3. Software and Tools for Computational Engineering, RWTH Aachen University, 52056, Aachen, Germany

    Uwe Naumann

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© 2008 Springer-Verlag Berlin Heidelberg

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Riehme, J., Walther, A., Stiller, J., Naumann, U. (2008). Adjoints for Time-Dependent Optimal Control. In: Bischof, C.H., Bücker, H.M., Hovland, P., Naumann, U., Utke, J. (eds) Advances in Automatic Differentiation. Lecture Notes in Computational Science and Engineering, vol 64. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68942-3_16

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