Abstract
This paper presents an adaptive threshold neural-network scheme for Rotorcraft Unmanned Aerial Vehicle (RUAV) sensor failure diagnosis. The approach based on adaptive threshold has the advantages of better detection and identification ability compared with traditional neural-network-based scheme. In this paper, the proposed scheme is demonstrated using the model of a RUAV and the results show that the adaptive threshold neural-network method is an effective tool for sensor fault detection of a RUAV.
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References
Song, Q., Qi, J.T., Han, J.D.: An adaptive UKF algorithm and its application in mobile robot control. In: Proceedings of the 2006 IEEE International Conference on Robotics and Biomimetics, pp. 1117–1122 (2006)
Kameyama, T., Ochi, Y.: Design of a failure tolerant flight control system with unscented kalman fliter. In: AIAA Guidance, Navigation, and Control Conference, AIAA-2005-6345 (2005)
Shin, J.Y., Wu, N.E., Belcastro, C.: Linear parameter varying control synthesis for actuator failure: based on estimated parameter. In: AIAA Guidance, Navigation, and Control Conference, AIAA-2002-4546 (2002)
Napolitano, R., An, Y., Seanor, B.: Kalman filters and neural-network schemes for sensor validation in flight control systems. IEEE Transaction on Control System Technology 6, 596–611 (1998)
Napolitano, R., An, Y., Seanor, B.: A fault tolerant flight control system for sensor and actuator failures using neural networks. Aircraft Design 3, 103–128 (2000)
Jakubek, S., Strasser, T.: Fault diagnosis using neural networks with ellipsoidal basis functions. In: Proceeding of American Control Conference, pp. 4513–4518 (2002)
Perhinschi, M.G., Napolitano, R., Campa, G., Fravolini, M.L.: An adaptive threshold approach for the design of an actuator failure detection and identification scheme. IEEE Transaction on Control System Technology 14, 519–525 (2006)
Qi, J.T., Zhao, X.G., Jiang, Z., Han, J.D.: Design and implement of a rotorcraft UAV test bed. In: Proceedings of the 2006 IEEE International Conference on Robotics and Biomimetics, pp. 109–144 (2006)
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Qi, J., Zhao, X., Jiang, Z., Han, J. (2007). An Adaptive Threshold Neural-Network Scheme for Rotorcraft UAV Sensor Failure Diagnosis. In: Liu, D., Fei, S., Hou, Z., Zhang, H., Sun, C. (eds) Advances in Neural Networks – ISNN 2007. ISNN 2007. Lecture Notes in Computer Science, vol 4493. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72395-0_73
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DOI: https://doi.org/10.1007/978-3-540-72395-0_73
Publisher Name: Springer, Berlin, Heidelberg
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