Adaptive Pitch Angle Tracking Control For Noncanonical Nonlinear Aircraft Systems

This study addresses the challenging problem of pitch angle tracking control for noncanonical nonlinear aircraft systems. Traditional control schemes for pitch angle tracking are primarily designed based on the Lyapunov function for canonical systems. However, due to the lack of information regarding the relative degree of controlled system, the design methods of traditional control schemes are not suitable for the noncanonical systems. To overcome this difficulty, this paper constructs a parameterizable high-order recurrent neural network to approximate the noncanonical nonlinear aircraft system so that the designed difficulty caused by unknown relative degree can be resolved. Based on the approximation system, we further propose. and proposes a novel gradient-based adaptive tracking control scheme based on this approximation system. By employing an advanced gradient adaptive update law and integrating parameter projection technology, the scheme can ensure asymptotic tracking performance and boundedness of all closed-loop signals. The controller can actively avoid potential singularities and enhance the robustness of the controller against model uncertainties and external disturbances. The simulation results based on the twin otter aircraft effectively demonstrate the significant effectiveness and superiority of the control scheme.