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Adaptive Neural Network Based on Finite-Time Attitude Control for Rigid Spacecraft during Orbit Maneuver

  • Harbin Institute of Technology
  • Aerospace System Engineering Shanghai

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

Abstract

Spacecraft performance of attitude control is influenced by orbit control force during orbit maneuver, and exerts an impact on orbit control. To maintain the stability of the system, an adaptive neural network attitude controller based on finite-time for rigid spacecraft is designed where a neural network is utilized to approximate the general disturbances including the drift of mass center, thruster misalignment, and parameter uncertainties. The finite-time stability of the closed-loop system is demonstrated by finite-time Lyapunov stability theory. Then, the controller is applied to the rigid spacecraft with uncertainties. The results of simulation show the effectiveness of the proposed control law. Key Words: Rigid spacecraft, neural network, finite-time.

Original languageEnglish
Title of host publicationProceedings of the 37th Chinese Control Conference, CCC 2018
EditorsXin Chen, Qianchuan Zhao
PublisherIEEE Computer Society
Pages3096-3101
Number of pages6
ISBN (Electronic)9789881563941
DOIs
StatePublished - 5 Oct 2018
Event37th Chinese Control Conference, CCC 2018 - Wuhan, China
Duration: 25 Jul 201827 Jul 2018

Publication series

NameChinese Control Conference, CCC
Volume2018-July
ISSN (Print)1934-1768
ISSN (Electronic)2161-2927

Conference

Conference37th Chinese Control Conference, CCC 2018
Country/TerritoryChina
CityWuhan
Period25/07/1827/07/18

Keywords

  • Finite-time control
  • Neural network
  • Rigid spacecraft

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