Skip to main navigation Skip to search Skip to main content

Neural adaptive integral sliding mode control for attitude tracking of flexible spacecraft with signal quantisation and actuator nonlinearity

  • Qiuhong Liu
  • , Ming Liu*
  • , Yan Shi
  • *Corresponding author for this work
  • School of Astronautics, Harbin Institute of Technology
  • Tokai University

Research output: Contribution to journalArticlepeer-review

Abstract

This study investigates the neural adaptive integral sliding mode control for attitude tracking of flexible spacecraft, where unknown actuator nonlinearity, input quantisation and external disturbances are considered simultaneously. In this design, the hysteresis encoder–decoder scheme is employed between the controller and actuator side for signal quantisation. A quantised adaptive integral sliding mode control strategy is developed, where the neural network scheme is applied to approximate the unmeasurable rigid-flexible coupled nonlinear dynamics. The proposed control strategy can compensate for quantisation error, actuator faults, actuator dead-zone as well as external disturbances effectively, and guarantee the trajectory of the attitude tracking error converge to the equilibrium point along the designed sliding surface. Finally, a simulation example is conducted to demonstrate the validness of the developed quantised control strategy for flexible spacecraft attitude tracking problem.

Original languageEnglish
Pages (from-to)2909-2921
Number of pages13
JournalInternational Journal of Systems Science
Volume51
Issue number15
DOIs
StatePublished - 17 Nov 2020
Externally publishedYes

Keywords

  • Flexible spacecraft control
  • actuator fault
  • adaptive integral sliding mode control
  • attitude tracking control
  • input quantisation
  • unknown actuator deadzone

Fingerprint

Dive into the research topics of 'Neural adaptive integral sliding mode control for attitude tracking of flexible spacecraft with signal quantisation and actuator nonlinearity'. Together they form a unique fingerprint.

Cite this