Predictive Control with Parameter Adaptation to Achieve α-Protection in the RECONFIGURE Benchmark in the Presence of Icing

Undetected ice accretions on aerodynamic surfaces can deeply change the dynamic behaviour of aircraft, leading to poor performance of the automatic control systems. This is characterised by oscillatory behaviour, and overshoot of setpoints and ight envelope protection values. To mitigate this undesirable behaviour, this paper applies predictive control in combination with online estimation of the first and second order partial derivatives of the lift and pitching moment coeffcients with respect to the angle of attack using an Extended Kalman Filter, to achieve a constrained indirect adaptive ight control law. The design is evaluated on the RECONFIGURE benchmark, which is a nonlinear, high fidelity, industrially validated simulator of a large Airbus aircraft. In icing scenarios at high incidence, the resulting trajectories are shown to be better damped and more compliant with constraints when compared to a predictive control law employing only linear disturbance estimation.