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Paper Count: 30184
Detection of Actuator Faults for an Attitude Control System using Neural Network
Abstract:The objective of this paper is to develop a neural network-based residual generator to detect the fault in the actuators for a specific communication satellite in its attitude control system (ACS). First, a dynamic multilayer perceptron network with dynamic neurons is used, those neurons correspond a second order linear Infinite Impulse Response (IIR) filter and a nonlinear activation function with adjustable parameters. Second, the parameters from the network are adjusted to minimize a performance index specified by the output estimated error, with the given input-output data collected from the specific ACS. Then, the proposed dynamic neural network is trained and applied for detecting the faults injected to the wheel, which is the main actuator in the normal mode for the communication satellite. Then the performance and capabilities of the proposed network were tested and compared with a conventional model-based observer residual, showing the differences between these two methods, and indicating the benefit of the proposed algorithm to know the real status of the momentum wheel. Finally, the application of the methods in a satellite ground station is discussed.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1076340Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1658
 R. Isermann "Fault-Diagnosis System," Springer-Verlag Berlin Heidelberg. 2006.
 R. Patton, F Uppal and C. Lopez-Toribio, "Soft computing approaches to fault diagnosis for dynamic systems: a survey," 4th. IFAC Symposium on fault Detection Supervision and Safety for technical processes, Budapest, Vol. 1, pp. 298-311, June 2000.
 S. Montenegro and K. Amezquita, "Accomplishing Station Keeping Mode for AOCS designed for T-SAT," Advances in Neural Network Research, The sixth ISNN 2009, Wuhan, China, pp. 507-516. Springer- Verlag, 2009.
 A. Alessandri, "Fault diagnosis for nonlinear systems using a bank of neural estimators," Computers in Industry, Vol. 52, No. 3, pp. 271 - 289, Dec. 2003.
 K. Patan, T. Parisini, "Identification of neural dynamic models for fault detection and isolation: the case of a real sugar evaporation process" Journal of Process Control, Vol. 15, No. 1, pp. 67 - 79, 2004.
 T. Sorsa, H. N. Koivo, and H. Koivisto, "Neural networks in process fault diagnostics," IEEE Transactions on Systems, Man, and Cybernetics, Vol. 21, No.4, 815 - 825, 1991.
 S. Simani, C. Fantuzzi and R. J. Patton, "Model-Based Fault Diagnosis in Dynamic Systems Using Identification Techniques," Springer 2003
 J. Wertz. "Spacecraft Attitude Determination and Control." Kluwer Academic Publishers, 1978.
 M. J. Sidi. "Spacecraft Dynamics and Control." Cambridge University Press, Cambridge New York, 1997
 B Bialke, "High fidelity mathematical modelling of reaction wheel performance," 21st Annual American Astronautical Society Guidance and Control Conference, pp. 483-486, Feb. 1998.
 W. Qing and S. Mehrdad "Model-based Robust Fault Diagnosis for Satellite Control Systems Using Learning and Sliding Mode Approaches," Journal of Computers, Vol. 4, No. 10, Simon Fraser University, Vancouver, BC, Canada. 2009.
 M. Ayoubi, "Fault diagnosis with dynamic neural structure and application to a turbo-charger," Proc. Int. Symp. Fault Detection Supervision and Safety for Technical Processes, AFEPROCESS'94, Espoo, Finland, Vol. 2, pp. 618 - 623, 1994.
 J. Korbicz, K. Patan, A. Obuchowicz, "Dynamic neural networks for process modeling in fault detection and isolation systems," International Journal of Applied Mathematics and Computer Science, Vol. 9, No. 3, pp. 519- 546, 1999.
 I. Al-Zyoud and K. Khorasani, "Neural network-based Actuactor Fault Diagnosis for Attitude Control Subsystem of an Unmanned Space Vehicle," International Joint Conference on Neural Networks, Vancouver, Canada. pp 3686-3693. July, 2006.
 Z. Li, L. Ma and K. Khorasani, "Dynamic Neural Network-Based Fault diagnosis for attitude control subsystem of a satellite," PRICAI, LNAI 4099, pp 308-318, Springer-Verlag Berlin Heidelberg 2006.
 Z. Li, L. Ma and K. Khorasani, "Fault Detection in Reaction Wheel of a satellite using Observer-Based Dynamic Neural Networks" ISNN 2005, LNCS 3498, pp. 584-590, Springer- Verlag Berling Heidelberg, 2005.
 T. Marcu, L Mirea and P. Frank, "Neural observer schemes for robust detection and isolation of process faults," UKACC International Conference on Control-98, September 1998. Conference Publication No. 455. IEEE, 1998.
 P. C. Hughes, "Spacecraft Attitude Dynamics." John Wiley & Sons (1986).
 V. Chobotov, "Spacecraft Attitude Dynamics and Control." Krieger Publishing Company. Malabar, Florida. USA. 1991.