Automatic interval management for aircraft based on dynamic fuzzy speed control considering uncertainty

Abstract

A novel real-time autonomous Interval Management System (IMS) is proposed to automate interval management, which considers the effect of wind uncertainty using the Dynamic Fuzzy Velocity Decision (DFVD) algorithm. The membership function can be generated dynamically based on the True Air Speed (TAS) limitation changes in real time and the interval criterion of the adjacent aircraft, and combined with human cognition to formulate fuzzy rules for speed adjusting decision-making. Three groups of experiments were conducted during the en-route descent stage to validate the proposed IMS and DFVD performances, and to analyze the impact factors of the algorithm. The verification experimental results show that compared with actual flight status data under controllers’ command, the IMS reduces the descent time by approaching 30% with favorable wind uncertainty suppression performance. Sensitivity analysis shows that the ability improvement of DFVD is mainly affected by the boundary value of the membership function. Additionally, the dynamic generation of the velocity membership function has greater advantages than the static method in terms of safety and stability. Through the analysis of influencing factors, we found that the interval criterion and aircraft category have no significant effect on the capability of IMS. In a higher initial altitude scenario, the initial interval should be appropriately increased to enhance safety and efficiency during the descent process. This prototype system could evolve into a real-time Flight-deck Interval Management (FIM) tool in the future.