KEYWORDS: Wavelets, Neural networks, Control systems, Missiles, Mathematical modeling, Aerodynamics, Complex systems, Nonlinear control, Control systems design, Lead
A new nonlinear control strategy incorporated the dynamic inversion method with wavelet neural networks is presented
for the nonlinear coupling system of Bank-to-Turn(BTT) missile in reentry phase. The basic control law is designed by
using the dynamic inversion feedback linearization method, and the online learning wavelet neural network is used to
compensate the inversion error due to aerodynamic parameter errors, modeling imprecise and external disturbance in
view of the time-frequency localization properties of wavelet transform. Weights adjusting laws are derived according to
Lyapunov stability theory, which can guarantee the boundedness of all signals in the whole system. Furthermore, robust
stability of the closed-loop system under this tracking law is proved. Finally, the six degree-of-freedom(6DOF)
simulation results have shown that the attitude angles can track the anticipant command precisely under the
circumstances of existing external disturbance and in the presence of parameter uncertainty. It means that the
dependence on model by dynamic inversion method is reduced and the robustness of control system is enhanced by
using wavelet neural network(WNN) to reconstruct inversion error on-line.
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