Trajectory tracking of a quadrotor helicopter based on L1 adaptive control

Li Min, Zuo Zongyu, Sun Donglei, Wang Chunyan, Wang Wei

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

3 Citations (Scopus)

Abstract

This paper presents an L1 adaptive controller to achieve the trajectory tracking for a quadrotor helicopter. The designed controller is based on nonlinear feed-forward compensations and uses a typical nonlinear quadrotor model considering uncertain inertial parameters and external disturbances. The L1 adaptive control design is slightly modified to comply with the position error dynamic and the attitude dynamic. The proposed L1 adaptive controller yields uniformly verifiable bounds on the transient and steady state tracking error for any designated bounded reference trajectory. In the presence of a fast adaptation, the adaptive controller with low-pass filters compensates for uncertainties and bounded disturbances in a particular frequency range. Finally, simulation results are included to validate the effectiveness of this control design.

Original languageEnglish
Title of host publicationCGNCC 2016 - 2016 IEEE Chinese Guidance, Navigation and Control Conference
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1887-1892
Number of pages6
ISBN (Electronic)9781467383189
DOIs
Publication statusPublished - 20 Jan 2017
Externally publishedYes
Event7th IEEE Chinese Guidance, Navigation and Control Conference, CGNCC 2016 - Nanjing, Jiangsu, China
Duration: 12 Aug 201614 Aug 2016

Publication series

NameCGNCC 2016 - 2016 IEEE Chinese Guidance, Navigation and Control Conference

Conference

Conference7th IEEE Chinese Guidance, Navigation and Control Conference, CGNCC 2016
Country/TerritoryChina
CityNanjing, Jiangsu
Period12/08/1614/08/16

Keywords

  • L Adaptive
  • Low-pass Filters
  • Quadrotor
  • Trajectory Tracking

Fingerprint

Dive into the research topics of 'Trajectory tracking of a quadrotor helicopter based on L1 adaptive control'. Together they form a unique fingerprint.

Cite this