Data-driven adaptive optimal output-feedback control of a 2-DOF helicopter

Weinan Gao, Zhong Ping Jiang

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

Abstract

This paper studies a data-driven adaptive optimal control problem of a Quanser's 2-degree-of-freedom (DOF) helicopter via output-feedback. A novel sampled-data-based approximate/adaptive dynamic programming (ADP) approach is developed. We start from a stabilizing controller computed using the bound of model uncertainties. Then the optimal control gain is iteratively learned by input/output information. The convergence of the proposed approach is theoretically ensured and the tradeoff between optimality and sampling period is rigorously studied as well. Finally, we show the performance of the proposed algorithm under bounded model uncertainties.

Original languageEnglish (US)
Title of host publication2016 American Control Conference, ACC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2512-2517
Number of pages6
ISBN (Electronic)9781467386821
DOIs
StatePublished - Jul 28 2016
Event2016 American Control Conference, ACC 2016 - Boston, United States
Duration: Jul 6 2016Jul 8 2016

Publication series

NameProceedings of the American Control Conference
Volume2016-July
ISSN (Print)0743-1619

Other

Other2016 American Control Conference, ACC 2016
CountryUnited States
CityBoston
Period7/6/167/8/16

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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