Adaptive sliding mode control for dual missile using RBF neural network

This paper presents an adaptive sliding mode control for a dual-controlled missile with tail fins and reaction jets. An RBF(Radial Basis Function) neural network is used to adaptively compensate for the uncertainties. The network adaptation rule is derived from Lyapunov stability theory. It is shown that the proposed control design achieves uniformly ultimate boundedness. The proposed controller is demonstrated by nonlinear missile dynamics and it shows a stable response against uncertainty.