An adaptive inverse controller for hypersonic vehicle

A neural network adaptive inverse controller structure is proposed to solve the problems that hypersonic aircraft with highly nonlinear and flight conditions of large span. OS-ELM algorithm is improved with RBF network for online learning and adaptive inverse controller for the on line training is used. Hypersonic aircraft with six degrees of freedom non-linear model is used to verify the performance of adaptive inverse controller. The controller based on flight conditions doing online learning in real time is shown with flight simulation in a typical condition. Aircraft orders tracking is achieved rapidly and steadyly and desired control effect is achieved.