Iterative Learning Control for Precise Aircraft Trajectory Tracking in Continuous Climb Operations

Abstract

In this paper, an iterative learning control method is used to improve precision in aircraft trajectory tracking in which, given a departure procedure, the dynamical model of an aircraft and a trajectory to be followed, the problem consists in defining an iterative learning control scheme which is able to improve the precision of the aircraft in following the trajectory taking into account the deviations suffered by previous flights. It is assumed that all the flights are operated with the same aircraft model and that they successively follow the same trajectory with short time-based separation and therefore are subject to similar recurrent disturbances. In the iterative learning control scheme used in this paper, the control action consists in generating at each iteration a new reference trajectory for the aircraft which compensates for recurrent disturbances. Thus, it can be applied to systems with underlying controllers for trajectory tracking, such as aircraft. In this case, the feedback trajectory tracking control is intended to reduce non-repetitive disturbances while the iterative learning control is intended to reject repetitive disturbances. The iterative learning control problem is solved in two steps: disturbance estimation and aircraft reference trajectory update. Both steps rely on a nominal model of the aircraft in which input and state constraints are explicitly taken into account. Continuous climb operations, defined within a standard instrumental departure, are considered in the simulations. The result show the effectiveness of the method which is able to reduce the trajectory tracking error due to recurrent disturbances in a few iterations, thus improving their predictability. Higher predictability of aircraft trajectories would simplify both management and control of air traffic, would improve the capacity of the air traffic management system and would allow a better exploitation of the infrastructures. Greater predictability of aircraft trajectories would also allow airlines to define and follow trajectories with a smaller number of alterations. This would result in a reduction of costs and emissions.