An Adaptive RBF Neural Guidance Law Surface to Air Missile Considering Target and Control Loop Uncertainties

A new guidance law for medium range homing missiles is developed by invoking the adaptive neural control theory. This approach is novel in that an integrated guidance-control model is derived to consider target maneuvers and missile dynamic uncertainties, also an RBF neural network is employed to adaptively compensate for the mentioned model nonlinearities. The network weights are adapted using a Lyapunov-based design. In addition an adaptive compensator is used in conjunction with the adaptive intelligent system for tolerating of the approximation errors and disturbance effects. This proposal yields a guidance law that is robust against different target maneuvers and in comparison to other introduced modern approaches is far easier to implement and need to a few numbers of inputs. Presented proof for the stability of guidance-control loop and simulated results demonstrate the effective performance of designed guidance law.