A Framework for Wind Sensitivity Analysis for Trajectory Tracking

Abstract

In this paper a sensitivity analysis of trajectories w.r.t. wind effects is proposed. This analysis will allow to specify wind estimates properties as well as control reactiveness characteristics to ensure accurate guidance in real atmosphere. The mathematic model developed for flight dynamics is intended to take into account wind gust effects on AoA, sideslip angle and airspeed. A two layer Nonlinear Dynamic Inversion (NDI) structure has been considered to control fast and slow dynamics. In order to test the proposed approach, a full six degrees of freedom Matlab model with trained Neural Networks to emulate a Boeing 737-200 was developed. where safety and traffic capacity issues are the milestones. Knowing that TBO relies on 4D guidance, it is not surprising that automation becomes one of the important enablers, allowing aircraft to follow more accurately a desired trajectory, resulting in a fuel usage decrease and reduced CO 2 emissions per flight. It is expected that 4D guidance improves safety by decreasing the occurrence of near mid-air collisions for planned conflict free 4D trajectories and in consequence, decrease the work load for air traffic controllers .Considering that one of the main disturbances during flight are wind gusts, it seems natural to take into account their effects while modelling aircraft dynamics. Once a mathematic model with wind contributions is obtained, a flight control structure must be assumed. In this work, a two-level Nonlinear Dynamic Inversion (NDI) has been developed to control the position and the angular velocities. The approach consists in transform algebraically a nonlinear system into a system with linear dynamics [3], [4]. Separation of slow and fast dynamics are common practice [5], [6]. Also, some machine learning algorithms and/or variations of the classical NDI approach have been tested in order to improve the performance of the method and provide robustness to uncertainties like modeling and/or measuring errors, showing good simulation results [7], [8]. However, full knowledge of variables and parameters cannot be acquired due to possible corrupted measures or uncertainty in parameters, leading to guidance inaccuracy. Thus, this work will provide a tool to quantify the performance of the aircraft in terms of position errors due to wind gusts by performing a sensitivity analysis through simulation. Actuator dynamics for the control surfaces involving a time-constant will also be considered.Methods to perform sensitivity analysis such as screening are common [9], where a baseline experiment is done using nominal values of parameters, then, selecting two extreme values of these, the results of the perturbed experiment w.r.t. the baseline are observed in order to decide to which parameters the model is most sensitive to. Nevertheless, interaction between parameters is neglected and the correlation between them and outputs of the system is considered linear. Variance-based approaches show how to find which are the most relevant parameters and how much they aff...

Controller for UAV to Oppose Different Kinds of Wind in the Environment

“…Side wind will cause the UAV to deviate from its desired course. In [10], Escamilla et al designs a trajectory tracker based on dynamic inverse control theory by analyzing wind properties and UAV control response efficiency. e data of wind speed is attained by the atmospheric prediction system.…”