Dynamic Neural Network-Based Pulsed Plasma Thruster (PPT) Fault Detection and Isolation for Formation Flying of Satellites
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Publisher
Springer Berlin Heidelberg
Link
http://link.springer.com/content/pdf/10.1007/978-3-540-85930-7_41
Reference20 articles.
1. Wilson, E., Lages, C., Mah, R.: Gyro-based Maximum-Likelihood Thruster Fault Detection and Identification. In: Proceedings of the 2002 American Control Conferences (2002)
2. Wilson, E., Sutter, D.W., Berkovitz, D., Betts, B.J., del Mundo, R., Kong, E., Lages, C.R., Mah, R., Papasin, R.: Motion-based System Identification and Fault Detection and Isolation Technologies for Thruster Controlled Spacecraft. In: Proceedings of the JANNAF 3rd Modeling and Simulation Joint Subcommittee Meeting (2005)
3. Piromoradi, F., Sassini, F., da Silva, C.W.: An Efficient Algorithm for Health Monitoring and Fault Diagnosis in a Spacecraft Attitude Determination System. In: IEEE International Conference on System, Man and Cybernetics, SMC (2007)
4. Larson, E.C., Parker Jr., B.E., Clark, B.R.: Model-Based Sensor and Actuator Fault Detection and Isolation. In: Proceedings of the American Control Conference (2002)
5. Joshi, A., Gavriloiu, V., Barua, A., Garabedian, A., Sinha, P., Khorasani, K.: Intelligent and Learning-based Approaches for Health Monitoring and Fault Diagnosis of RADARSAT-1 Attitude Control System. In: IEEE Int. Conf. on System, Man and Cybernetics, SMC (2007)
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