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30 October 2009 Adaptive dynamic inversion robust control for BTT missile based on wavelet neural network
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Proceedings Volume 7496, MIPPR 2009: Pattern Recognition and Computer Vision; 74961D (2009)
Event: Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, 2009, Yichang, China
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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Chuanfeng Li, Yongji Wang, Zhixiang Deng, and Hao Wu "Adaptive dynamic inversion robust control for BTT missile based on wavelet neural network", Proc. SPIE 7496, MIPPR 2009: Pattern Recognition and Computer Vision, 74961D (30 October 2009);

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