Fault Detection, Isolation and Identification of Formation Flying Satellites using Wavelet-Entropy and Neural Networks
The main objective of this thesis is to develop a fault detection, isolation and identification (FDII) scheme based on Wavelet Entropy (WE) and Artificial Neural Network (ANN) for reaction wheels (RW) that are employed as actuators in the attitude control subsystem (ACS) of a satellites to perform t...
Similar Items
-
Dynamic neural network-based pulsed plasma thruster (PPT) fault detection and isolation for the attitude control subsystem of formation flying satellites
by: Valdes, Arturo
Published: (2008) -
Fault Identification of Gearbox Degradation with Optimized Wavelet Neural Network
by: Hanxin Chen, et al.
Published: (2013-01-01) -
Identification of Power System Fault Using Wavelet Transform and Neural Network
by: Wei-Tsung Hsu, et al.
Published: (2003) -
Neural Network-based Fault Diagnosis of Satellites Formation Flight
by: Mousavi Mirak, Shima
Published: (2013) -
Fault detection and identification using fuzzy wavelets
by: Mufti, Muid Ur-Rahman
Published: (2007)