Design for BTT Missile Controller Base on the RBF Neural Networks

In this paper, adaptive RBF neural networks are present for nonlinear BTT missile controller. Considering the unknown smooth function vectors and the uncertainty of pneumatic parameter , we introduce RBF neural networks to simulate this nonlinear vectors. It overcomes some limitations of robust control. Furthurmore, a systematic backstepping design method has been used to ultimately guarantee semileptonically uniformly bounded of closed loop signals, and the output of system can converge to a small neighborhood of the actual trajectory. Finally, the simulation result is presented to demonstrate the validity of the approach.