A data-driven indirect method for nonlinear optimal control

Gao Tang, Kris Hauser

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Nonlinear optimal control problems are challenging to solve due to the prevalence of local minima that prevent convergence and/or optimality. This paper describes nearest-neighbors optimal control (NNOC), a data-driven framework for nonlinear optimal control using indirect methods. It determines initial guesses for new problems with the help of precomputed solutions to similar problems, retrieved using k-nearest neighbors. A sensitivity analysis technique is introduced to linearly approximate the variation of solutions between new and precomputed problems based on their variation of parameters. Experiments show that NNOC can obtain the global optimal solution orders of magnitude faster than standard random restart methods, and sensitivity analysis can further reduce the solving time almost by half. Examples are shown on two optimal control problems in vehicle control.

Original languageEnglish (US)
Title of host publicationIROS 2017 - IEEE/RSJ International Conference on Intelligent Robots and Systems
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4854-4861
Number of pages8
ISBN (Electronic)9781538626825
DOIs
StatePublished - Dec 13 2017
Externally publishedYes
Event2017 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2017 - Vancouver, Canada
Duration: Sep 24 2017Sep 28 2017

Publication series

NameIEEE International Conference on Intelligent Robots and Systems
Volume2017-September
ISSN (Print)2153-0858
ISSN (Electronic)2153-0866

Other

Other2017 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2017
CountryCanada
CityVancouver
Period9/24/179/28/17

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Computer Vision and Pattern Recognition
  • Computer Science Applications

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  • Cite this

    Tang, G., & Hauser, K. (2017). A data-driven indirect method for nonlinear optimal control. In IROS 2017 - IEEE/RSJ International Conference on Intelligent Robots and Systems (pp. 4854-4861). [8206362] (IEEE International Conference on Intelligent Robots and Systems; Vol. 2017-September). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IROS.2017.8206362