A flatness based flight guidance control using neural networks

The increasing air traffic flow around most airports of regional hubs and big cities worldwide inevitably leads to saturation problems and strongly drives the researchers to find out new solutions to this issue. In this communication, we try to propose a solution to this problem from the standing of flight guidance control approach. The differentially flat system theory is introduced as the basis of the proposed flight guidance control approach. In this study, the differential flatness property of flight guidance dynamics is presented. With the help of neural networks to numerically resolve the implicit dynamic equations, the nominal guidance control input can be obtained. With the considerable generalization problem, modeling errors and anticipated disturbance in practical application, an additional feedback loop is implemented to improve the trajectory tracking performance. The preliminary simulation results for vertical trajectory tracking display the feasibility of this flatness based neural flight guidance control scheme.