Skip to main navigation Skip to search Skip to main content

Nonlinear Model Predictive Control for Spacecraft Attitude Tracking with Kalman Filter

  • Harbin Institute of Technology Shenzhen

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

Abstract

This technical paper provides an attitude tracking strategy by employing a nonlinear model predictive controller (NMPC). To directly use the relative navigation information, the piecewise affine (PWA) model based on the Euler dynamics is adopted. Due to the singularity of Euler angles, a singularity-free strategy is proposed to complete continuous attitude tracking. Consider the sensor uncertainty and disturbance, the Kalman filter is combined with the NMPC framework. Finally, the numerical results are presented to show the control performance.

Original languageEnglish
Title of host publicationProceedings - 2020 Chinese Automation Congress, CAC 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3389-3394
Number of pages6
ISBN (Electronic)9781728176871
DOIs
StatePublished - 6 Nov 2020
Externally publishedYes
Event2020 Chinese Automation Congress, CAC 2020 - Shanghai, China
Duration: 6 Nov 20208 Nov 2020

Publication series

NameProceedings - 2020 Chinese Automation Congress, CAC 2020

Conference

Conference2020 Chinese Automation Congress, CAC 2020
Country/TerritoryChina
CityShanghai
Period6/11/208/11/20

Keywords

  • Attitude tracking
  • NMPC
  • singularity-free

Fingerprint

Dive into the research topics of 'Nonlinear Model Predictive Control for Spacecraft Attitude Tracking with Kalman Filter'. Together they form a unique fingerprint.

Cite this