Neural network adaptive inversion control law design for a supermaneuverable aircraft

A discrete time neural network adaptive inversion controller design for a supermaneuverable aircraft nonlinear model is presented. The singular perturbation theory is used to separate the nonlinear dynamics into fast and slow sub-systems; The dynamic inversion is applied to design the control laws for the two sub-systems separately; The neural network adaptive control is based on the dynamic inversion, and the inversion error of system is compensated by the off-line neural network. To evaluate the control performance, the maneuver generator is designed to simulate the pilot inputs. The simulation results show that the designed control law can ensure the stability of the closed-loop system, and tracks the inputs well. The design takes into account the multi input multi output nature of the model. Nonlinear simulation results are given to prove the effectiveness of the controller.