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Spacecraft attitude control based on generalised dynamic inversion with adaptive neural network

Published online by Cambridge University Press:  31 August 2023

S. M. N. Jafri Open the ORCID record for S. M. N. Jafri [Opens in a new window]  and
M. I. Aslam Open the ORCID record for M. I. Aslam [Opens in a new window]
S. M. N. Jafri*
Affiliation:
Department of Electronic Engineering, NED University of Engineering and Technology, Karachi, Pakistan
M. I. Aslam
Affiliation:
Department of Telecommunications Engineering, NED University of Engineering and Technology, Karachi, Pakistan
*
Corresponding author: S. M. N. Jafri; Email: jafri_minhaj@cloud.neduet.edu.pk
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Abstract

This paper proposes a robust generalised dynamic inversion (GDI) control system design with adaptive neural network (NN) estimation for spacecraft attitude tracking under the absence of knowledge of the spacecraft inertia parameters. The robust GDI control system works to enforce attitude tracking, and the adaptive NN augmentation compensates for the lack of knowledge of the spacecraft inertia parameters. The baseline GDI control law consists of a particular part and an auxiliary part. The particular part of the GDI control law works to realise a desired attitude dynamics of the spacecraft, and the auxiliary part works for finite-time stabilisation of the spacecraft angular velocity. Robustness against modeling uncertainties and external disturbances is provided by augmenting a siding mode control element within the particular part of the GDI control law. The singularity that accompanies GDI control is avoided by modifying the Moore-Penrose generalised inverse by means of a dynamic scaling factor. The NN weighting matrices are updated adaptively through a control Lyapunov function. A detailed stability analysis shows that the closed loop system is semi-global practically stable. For performance assessment, a spacecraft model is developed, and GDI-NN control is investigated for its attitude control problem through numerical simulations. Simulation results reveal the efficacy, robustness and adaptive attributes of proposed GDI-NN control for its application to spacecraft attitude control.

Keywords

spacecraft attitude controlgeneralized dynamic inversionsliding mode controlneural networks
Type
Research Article
Information
The Aeronautical Journal , Volume 128 , Issue 1321 , March 2024 , pp. 504 - 516
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Copyright
© The Author(s), 2023. Published by Cambridge University Press on behalf of Royal Aeronautical Society

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