Robust adaptive control based on wavelet neural network for a hypersonic vehicle

In order to enhance robustness of dynamic inversion controller for a general hypersonic vehicle, a stable robust adaptive control strategy based on wavelet neural network is proposed. An adaptive term implements by the wavelet neural network output to approximately cancel uncertainties, and also a robust term is designed to attenuate the approximation error with guaranteed performance and stability. The system asymptotically tracks the desired output by means of on-line studying uncertainties via wavelet neural network. Theoretical analysis is done to validate Lyapunov stability of the system. The simulation results show that the developed method can provide sufficient robustness and adaptability. This method is effective and deals with the problem of uncertain parameters preferably.