Abstract
Most fault detection and accommodation methods have traditionally been derived based on linear system modeling techniques, which restrict the type of practical failure situation that can be modeled. In this paper we explore a methodology for fault accommodation in nonlinear dynamic systems. A new control scheme is derived by incorporating two neural network (NN) units to effectively attenuate and compensate uncertain dynamics due to unpredictable faults. It is shown that the method is independent of the nature of the fault. Numerical simulations are included to demonstrate the effectiveness of the proposed method.
This work was supported in part by NSF under the HBCU-RISE program (Award number HRD-0450203).
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© 2005 Springer-Verlag Berlin Heidelberg
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Song, Y.D., Liao, X.H., Bolden, C., Yang, Z. (2005). Dealing with Fault Dynamics in Nonlinear Systems via Double Neural Network Units. In: Wang, J., Liao, XF., Yi, Z. (eds) Advances in Neural Networks – ISNN 2005. ISNN 2005. Lecture Notes in Computer Science, vol 3498. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11427469_14
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DOI: https://doi.org/10.1007/11427469_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25914-5
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