Abstract
Built on the existing framework, we propose a novel supervisory system capable of detecting controller malfunctions before the stability of the plant is compromised. Furthermore, due to its ability to discern between controller malfunctions and faults within the plant, the proposed supervisor acts in a specific fashion in the event of a controller malfunction to provide new avenues with a greater probability of convergence using information from a Dynamic Model Bank. The classification and distinction of controller malfunctions from the faults in the plant itself is achieved through an advanced decision logic based on three independent quality indexes. Proof-of-the-concept simulations over a nonlinear plant demonstrate the validity of the approach.
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© 2005 Springer-Verlag Berlin Heidelberg
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Yen, G.G. (2005). Adaptive Critic for Controller Malfunction Accommodation. 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_11
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DOI: https://doi.org/10.1007/11427469_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25914-5
Online ISBN: 978-3-540-32069-2
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