Asymptotic tracking for aircraft via an uncertain Dynamic Inversion method

An asymptotic tracking controller is designed in this paper, which combines model reference adaptive control (MRAC) and dynamic inversion (DI) methodologies in conduction with the robust integral of the signum of the error (RISE) technique for output tracking of an aircraft system in the presence of parametric uncertainty and unknown, nonlinear disturbances, which are not linearly parameterizable (non- LP). The control design is complicated by the fact that the control input is multiplied by an uncertain, non-square matrix. Partial knowledge of the aircraft model along with constant feedforward estimates of the unknown plant parameters are exploited in order to reduce the required control effort. This result shows for the first time how asymptotic tracking control can be achieved for a nonlinear system in the presence of a non-square input matrix containing parametric uncertainty and nonlinear, non-LP disturbances. Asymptotic output tracking is proven via Lyapunov stability analysis, and high-fidelity simulation results are provided to verify the efficacy of the proposed controller.