Dynamic Recurrent Neural Networks for Stable Adaptive Control of Wing Rock Motion

Abstract

Wing Rock or limit cycle oscillation (LCO) in an aircraft is often caused by aerodynamic nonlinearities or mechanical hysteresis. A dynamic recurrent radial basis function neural networ~s (DR-RBF) are proposed for modelling the nonlinear hysteresis. The concept based on Preisach hysteresis model is used in the design of neural networks. The structure and memory mechanism in the hysteresis model is analogous to parallel connectivity and memory formation in neural networks. Adaptive control law based on minimisation of the energy function to ensure stability in the Lyapunov sense is presented.