Skip to main content

Continuous Optimal Control Sensitivity Analysis with AD

  • Chapter
  • First Online:

Abstract

In order to apply a parametric method to a minimum time control problem in celestial mechanics, a sensitivity analysis is performed. The analysis is continuous in the sense that it is done in the infinite dimensional control setting. The resulting sufficient second order condition is evaluated by means of automatic differentiation, while the associated sensitivity derivative is computed by continuous reverse differentiation. The numerical results are given for several examples of orbit transfer, also illustrating the advantages of automatic differentiation over finite differences for the computation of gradients on the discretized problem.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   54.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2002 Springer Science+Business Media New York

About this chapter

Cite this chapter

Caillau, JB., Noailles, J. (2002). Continuous Optimal Control Sensitivity Analysis with AD. In: Corliss, G., Faure, C., Griewank, A., Hascoët, L., Naumann, U. (eds) Automatic Differentiation of Algorithms. Springer, New York, NY. https://doi.org/10.1007/978-1-4613-0075-5_11

Download citation

  • DOI: https://doi.org/10.1007/978-1-4613-0075-5_11

  • Published:

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4612-6543-6

  • Online ISBN: 978-1-4613-0075-5

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics