Nonlinear adaptive flight control law design and handling qualities evaluation

This paper considers the design of a stability and control augmentation system for a modern fighter aircraft. The aim of the flight control system is to offer the pilot consistent good flying and handling qualities over a specified flight envelope and to provide robustness to model uncertainties. A nonlinear adaptive backstepping method is proposed to directly deal with the nonlinearities and the uncertainties of the system. B-spline neural networks are used to partition the flight envelope into multiple connecting regions. In each partition a locally valid linear-in-the-parameters nonlinear aircraft model is defined, of which the unknown parameters are approximated online by Lyapunov based update laws. These update laws take aircraft state and input constraints into account so that they do not corrupt the parameter estimation process. The desired aircraft response characteristics are enforced with command filters and verified by applying conventional handling qualities analysis techniques to numerical simulation data. Simulation results show that the controller is capable of giving desired closed-loop nominal and robust performance in the presence of aerodynamic uncertainties.