Dynamically structured radial basis function neural networks for robust aircraft flight control

An online control scheme that utilizes a dynamically structured radial basis function network (RBFN) is developed for aircraft control. By using Lyapunov synthesis approach, the tuning rule for updating all the parameters of the dynamic RBFN which guarantees the stability of the overall system is derived. The robustness of the proposed tuning rule is also analyzed. Simulation studies using the F8 aircraft longitudinal model demonstrates the efficiency of the method and also show that with a dynamically structured RBFN, a more compact network structure can be implemented.