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System identification based on DNNs with disturbance observer and application to unmanned aerial vehicles

  • Yang Yi
  • , Weixing Zheng
  • , Yi Yang
  • , Lei Guo
  • Southeast University, Nanjing
  • Western Sydney University
  • Beihang University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper, dynamic neural networks (DNNs) are used as the on-line identifier for a class of nonlinear systems with unknown external disturbance and unknown multiple dead zone actuators. By integrating the novel nonlinear disturbance observer with adaptive control algorithms, the parameter coupling problem between unknown dead zone and DNNs can be successfully solved and the multiple disturbances can also be rejected simultaneously. Both the observation error and the identification error can be proved to convergent to zero. Furthermore, by combining with the numerical result of an unmanned aerial vehicle (UAV) model, the effectiveness of theoretical algorithms can be fully verified.

Original languageEnglish
Title of host publicationProceedings of the 32nd Chinese Control Conference, CCC 2013
PublisherIEEE Computer Society
Pages1787-1791
Number of pages5
ISBN (Print)9789881563835
StatePublished - 18 Oct 2013
Event32nd Chinese Control Conference, CCC 2013 - Xi'an, China
Duration: 26 Jul 201328 Jul 2013

Publication series

NameChinese Control Conference, CCC
ISSN (Print)1934-1768
ISSN (Electronic)2161-2927

Conference

Conference32nd Chinese Control Conference, CCC 2013
Country/TerritoryChina
CityXi'an
Period26/07/1328/07/13

Keywords

  • Dead zone disturbance
  • Disturbance observer
  • Dynamic neural networks
  • System identification
  • Unmanned aerial vehicles

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