Adaptive Neural Network-Based Satellite Attitude Control by Using the Dynamic Inversion Technique and a VSCMG Pyramidal Cluster. (6th January 2019)

• Record Type: Journal Article
• Authors: Lungu, Mihai; Lungu, Romulus
• Other Names: Sahoo Avimanyu Academic Editor.
• Is Part Of: Complexity. Volume 2019(2019)
• Publication Date: 2019-01-06
• Subjects: Chaotic behavior in systems -- Periodicals; Complexity (Philosophy) -- Periodicals; 003
• DOI: 10.1155/2019/1645042
• Languages: English
• ISSNs: 1076-2787

Abstract

Abstract : The paper presents an adaptive system for the control of small satellites' attitude by using a pyramidal cluster of four variable-speed control moment gyros as actuators. Starting from the dynamic model of the pyramidal cluster, an adaptive control law is designed by means of the dynamic inversion method and a feed-forward neural network-based nonlinear subsystem; the control law has a proportional-integrator component (for the control of the reduced-order linear subsystem) and an adaptive component (for the compensation of the approximation error associated with the function describing the dynamics of the nonlinear system). The software implementation and validation of the new control architecture are achieved by using the Matlab/Simulink environment.