Adaptive Quaternion Attitude Control of Aerodynamic Flight Control Vehicles

Conventional quaternion based methods have been extensively employed for spacecraft attitude control where the aerodynamic forces can be neglected. In the presence of aerodynamic forces, the flight attitude control is more complicated due to aerodynamic moments and inertia uncertainties. In this paper, a robust nero-adaptive quaternion controller based on back-stepping technique for vehicle with aerodynamic actuators is proposed. The presented control lawconsists of a neural network based adaptive part and an additional term which ensures the robustness of the system. Actually, the first term is designed to approximate and cancel out the matched uncertainties and the second term is used  toensure the robustness of system against approximation error of the neural network.The Lyapunov direct method is applied to derive the learning laws for the neural network weights and adaptive gain. Also,theultimately boundedness of the error signals is guaranteed based on theLyapunov’s  stability criterion. The benefit of the presented method is evaluated through simulation of an aerodynamic control vehicle.