Identification and control of aircraft dynamics using radial basis function networks
Date
1993ISBN
0-7803-0908-1Publisher
Publ by IEEESource
Proceedings of the IEEE Conference on Control ApplicationsProceedings of the IEEE Conference on Control Applications. Part 2 (of 2)
Volume
2Pages
567-572Google Scholar check
Keyword(s):
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In this paper, we investigate one type of neural networks, namely the Radial Basis Functions (RBF) networks, and apply them to the identification and control problems of an aircraft system. The RBF network is used as an on-line-approximator of the aircraft pitch dynamics, combined with a nonlinear control law to improve the closed-loop system performance. The result are illustrated through simulations using a nonlinear model of the F-16 aircraft pitch dynamics.