Unmanned Aerıal Vehicles Landing Sequencing Modelling Via Fuzzy Logic Air Traffic Controllers are decision maker in dynamic and complex environment including numerous actors, consistent updating of pertinent data. They need to decide in a short time with incomplete information, under time pressure and high workload. Basically for sequencing and separating the aerial vehicles there are some inputs like speed, altitude, distance, rate of descend, endurance etc. On the other hand universal rules for sequencing and separating cannot be omitted. But finally we have only one output: “Who will be the number one for landing?” In that point, we propose a new model via fuzzy logic. The determination of conflicts between aircraft can be regarded as a very complex problem, yet air traffic controllers have the capacity to perform the undertaking with high rates of accomplishment under demanding circumstances. Much of the expertise of the air traffic controller appears to lie in the capacity to choose the suitable methodology for the issue. In this paper, we present an analytic approach for UAV landing sequencing modelling with in the dynamic airspace including different mission types or applications for both military and civilian vehicles. For modelling, we utilize the MATLAB Fuzzy FIS (Fuzzy Inference System) with realistic data and create the user friendly interface with MATLAB/GUI. The simulation results show that the proposed model is a robust alternative for maximum mission efficiency, minimum fuel consumption and delay reduction. İnsansız Hava Araçları İniş Sıralamasının Bulanık Mantık Modellemesi Bir hava trafik kontrolörü, hava trafik yönetiminin emniyetli, etkin ve süratli bir şekilde sağlanmasından sorumludur. Hava trafik kontrolörlerinin en önemli görevlerinden biri emniyetli bir uçuş için hava araçları arasındaki mesafelendirmeyi diğer bir ifade ile ayırmayı doğru olarak sağlayabilmesidir. Emniyetin yanı sıra trafik akışının hız ve verimliliğini temin etmek de kontrolörün amacıdır. Hava trafik kontrolörünün amacına ulaşması birçok karmaşık uygulama, planlama, karar verme, iletişim ve koordinasyon faaliyetlerinin en iyi şekilde gerçekleştirmesine bağlıdır. Bu da hava trafik kontrolörlerin çalışma ortamını çok karmaşık ve dolayısıyla hatalara yatkın hale getirmektedir. Bu çalışmada, insansız hava araçları iniş sıralaması için önerilen bulanık mantık modellemesinin tasarım aşamasında MATLAB/FIS (Fuzzy Inference System – Bulanık Mantık Arayüzü) editörü kullanılmıştır. Bulanıklaştırma arayüzünün üyelik fonksiyonları olarak, iniş sıralamasına etki eden altı adet parametrenin sayısal değerlerine karşılık gelen üçgen ve yamuk üyelik fonksiyonları kullanılmıştır. Bunun yanı sıra belirlenen üyelik fonksiyonları normal, monoton ve simetriktir. Çıkarım motorunda Min-Max Metodu ile Mamdani Yöntemi, durulama arayüzünde ise Ağırlık Merkezi Yöntemi kullanılmıştır. Bulanık mantık tabanlı modellemenin oluşturulmasından sonra hava trafik kontrolörlerinin insansız hava araçlarına ait verileri işleyerek daha hızlı ve kolay bir şekilde sonuca ulaşmalarını sağlayacak altı adet insansız hava aracı bilgilerinin girilebildiği kullanıcı arayüzü MATLAB/GUI yardımıyla tasarlanmıştır.
Unmanned Air Vehicles Landing Sequencing Modelling Via Fuzzy Logic Air Traffic Controllers are decision maker in dynamic and complex environment including numerous actors, consistent updating of relevant data. They need to decide in a short time with incomplete information, under time pressure and high workload. Basically for sequencing and separating the air vehicles there are some inputs like speed, altitude, distance, rate of descend, endurance etc. On the other hand, universal rules for sequencing and separating cannot be omitted. But finally we have only one output: "Who will be the number one for landing?" In that point, we propose a new model via fuzzy logic. The determination of conflicts between aircraft can be regarded as a very complex problem, yet air traffic controllers have the ability to perform the undertaking with high rates of accomplishment under demanding circumstances. Much of the expertise of the air traffic controller appears to lie in the ability to choose the suitable methodology for the issue. In this paper, we present an analytical approach for UAV landing sequencing modelling with in the dynamic airspace including different mission types or applications for both military and civil vehicles. For modeling, we use the MATLAB Fuzzy FIS (Fuzzy Inference System) with realistic data and create the user-friendly interface with MATLAB/GUI. The simulation results show that the proposed model is a robust alternative for maximum mission efficiency, minimum fuel consumption and delay reduction. A air traffic controller is responsible for ensuring air traffic management in a safe, efficient and rapid way. One of the most important tasks of air traffic controllers is to ensure that the distance between aircraft is properly separated by another expression for a secure flight. In addition to safety, it is also the controller’s goal to ensure the speed and efficiency of traffic flow. The achievement of the goal of the air traffic controller depends on the best performance of many complex implementation, planning, decision-making, communication and coordination activities. This also makes the working environment of air traffic controllers very complex and therefore prone to errors. In this study, the editor MATLAB/FIS (Fuzzy Inference System) was used in the design phase of the suggested mock logic modeling for the landing ranking of unmanned aircraft. As the membership functions of the clustering interface, the triangle and thumb membership functions that correspond to the numerical values of the six parameters affecting the landing ranking have been used. In addition, the determined membership functions are normal, monotonous and symmetrical. The exhaust engine uses the Min-Max method, and the weight center method is used in the washing interface. After the creation of the logic-based modeling, the air traffic controller’s user interface is designed with the help of MATLAB/GUI, where six unmanned aircraft information can be entered, which will help them process the data of the unmanned aircraft in a faster and easier way to reach the outcome.
Alan : Fen Bilimleri ve Matematik; Mühendislik
Dergi Türü : Uluslararası
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