Launch vehicle adaptive flight control with incremental model based heuristic dynamic programming

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

5 Citations (Scopus)

Abstract

A self-learning controller which makes quick and successful adaptations to new conditions can considerably benefit autonomous operations of launch vehicles. To provide a model-free, adaptive process for optimal control, approximate dynamic programming has been introduced to aerospace engineering. A widely used structure of approximate dynamic programming for nonlinear systems is heuristic dynamic programming. This paper proposes a new method using incremental models in heuristic dynamic programming to improve the online learning capacity. This method generates an adaptive near-optimal controller online without a priori knowledge of the system dynamics or off-line learning of the system model. A comparison is made between the conventional heuristic dynamic programming algorithm and the incremental model based heuristic dynamic programming algorithm by applying them to an online flight control problem with an unknown nonlinear model. The results demonstrate that the incremental model based heuristic dynamic programming method accelerates online learning, improves the precision, and can deal with a wider range of initial states compared to the conventional heuristic dynamic programming method.

Original languageEnglish
Title of host publication68th International Astronautical Congress, IAC 2017
Subtitle of host publicationUnlocking Imagination, Fostering Innovation and Strengthening Security
PublisherInternational Astronautical Federation, IAF
Pages7154-7164
Number of pages11
Volume11
ISBN (Print)9781510855373
Publication statusPublished - 1 Jan 2017
Event68th International Astronautical Congress: Unlocking Imagination, Fostering Innovation and Strengthening Security, IAC 2017: Unlocking Imagination, Fostering Innovation and Strengthening Security - Adelaide, Australia
Duration: 25 Sep 201729 Sep 2017
Conference number: 68
http://www.iafastro.org/events/iac/iac-2017/

Conference

Conference68th International Astronautical Congress: Unlocking Imagination, Fostering Innovation and Strengthening Security, IAC 2017
Abbreviated titleIAC 2017
CountryAustralia
CityAdelaide
Period25/09/1729/09/17
Internet address

Keywords

  • Adaptive flight control
  • Heuristic dynamic programming
  • Incremental techniques
  • Nonlinear control
  • Online learning

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