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- W2029604320 abstract "Based on fully tuned RBF neural networks and backstepping control techniques, a novel nonlinear adaptive control scheme is proposed for missile control systems with a general set of uncertainties. The effect of the uncertainties is synthesized one term in the design procedure. Then RBF neural networks are used to eliminate its effect. The nonlinear adaptive controller is designed using backstepping control techniques. The control problem is resolved while the control coefficient matrix is unknown. The adaptive tuning rules for updating all of the parameters of the fully tuned RBF neural networks are firstly derived by the Lyapunov stability theorem. Finally, nonlinear 6-DOF numerical simulation results for a BTT missile model are presented to demonstrate the effectiveness of the proposed method." @default.
- W2029604320 created "2016-06-24" @default.
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- W2029604320 date "2003-09-03" @default.
- W2029604320 modified "2023-09-27" @default.
- W2029604320 title "Nonlinear adaptive control systems design of BTT missile based on fully tuned RBF neural networks" @default.
- W2029604320 doi "https://doi.org/10.1117/12.521986" @default.
- W2029604320 hasPublicationYear "2003" @default.
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