Resumen de Iterative learning control for precise aircraft trajectory tracking

Almudena José Buelta Méndez

• The aim of this thesis is to apply iterative learning control to achieve high overall precision in commercial aircraft trajectory tracking in the presence of unknown disturbances, measurement noise, model uncertainties and even when the dynamic model of the aircraft changes along the iterations.

  More specifically, an optimization-based ILC scheme is applied to precise trajectory tracking for commercial fixed-wing aircraft flying in realistic operational scenarios, proving the effectiveness of this approach to compensate for repetitive disturbances.

  A combined MRAC-ILC framework transfers the knowledge acquired by an aircraft in following a planned trajectory to a different aircraft, so that, in the following iteration, the ILC can compensate for the recurrent disturbances even if the tajectory is tracked by an aircraft with different model dynamics.