LEE- Savunma Teknolojileri Lisansüstü Programı

Bu topluluk için Kalıcı Uri

http://hdl.handle.net/11527/19450

Gözat

Konu "aircraft" ile LEE- Savunma Teknolojileri Lisansüstü Programı'a göz atma
  • Öge
    Fighter pilot behavior cloning and transferring to another aircraft
    (Graduate School, 2022) Sever, Gülay ; Üre, Nazım Kemal ; 772812 ; Autonomous Systems Programme
    he "Pilot-in-the-loop" flight simulators are important tools in the development of fighter aircraft because they allow engineers and designers to test different scenarios and algorithms in a controlled environment without the risks associated with actual flight testing. However, these simulations often require high pilot skill levels and can be time-consuming and costly to arrange. It is important to create realistic models of human fighter pilots in order to reduce the reliance on skilled pilots to demonstrate agile/aerobatic maneuvers in flight simulators. Traditional controllers for aircraft require detailed knowledge about the aerodynamic model and physics of the aircraft in order to perform aerobatic maneuvers. Also, these control algorithms may not be able to match the performance of skilled human pilots, who are limited by a lack of bandwidth. This suggests that there may be potential for improving the performance of aircraft through the use of techniques that can take advantage of the superior speed and maneuverability of skilled pilots. In that case, imitation learning is a potential solution to eliminate the dependency need of skillful pilots in the flight simulator. Imitation learning also known as learning from demonstrations has benefited from computational progresses brought on by deep learning and increased availability of demonstration data. It is aimed to emulate desired behavior in a given task. An agent is trained to learn mapping between observations and actions by utilizing demonstrations. In this thesis aims the development of a pilot behavior model which is capable of autonomously performing agile maneuvers and is able to replace expert pilots' demonstrations over its full flight envelope in the flight simulator. Moreover, this model is transferable to other aircraft with limited data using transfer learning techniques. Besides all these features, the pilot behavior model can be able to run in real time in the flight simulator.
  • Öge
    Online loss of control prevention of an agile aircraft: Lyapunov-based dynamic command saturation approach
    (Graduate School, 2023-05-17) Altunkaya, Çağrı Ege ; Özkol, İbrahim ; 514211003 ; Savunma Teknolojileri
    Over the past few decades, the combat arena has witnessed the updating of military doctrines. In particular, air combat paradigms have been renewed in terms of pioneering air vehicles and air combat tactics. Ancient air-to-air combat maneuvers have been replaced by new, astonishing maneuvers that require more pilot skill and state-of-the-art fighter aircraft in terms of both aerodynamics and flight control. Consequently, advancing maneuvering capability seems to be one of the key features in increasing the survivability of fighter aircraft during dogfights. However, this request brings several prerequisites, including struggling with generated uncertainties because of highly nonlinear aerodynamic characteristics, besides flight dynamics. Another prerequisite is ensuring flight safety throughout the mission, even during the most agile maneuvers, which is the main issue of this study. An agile maneuvering aircraft is inherently expected to perform its mission in the most effective and safe manner, especially a fighter aircraft that carries out outstanding and challenging operations. During these operations, the aircraft is exposed to extremely nonlinear effects sourced from aerodynamics and flight dynamics. As is commonly known, classical linear flight control methods are not capable of dealing with these nonlinear effects because linear flight controllers are designed around an equilibrium point. As the states of the aircraft get far away from that designed equilibrium point, the controller's performance degrades dramatically. Therefore, many nonlinear control methods have been adopted for agile aircraft in the literature and even in the real world. In this study, the incremental nonlinear dynamic inversion technique is adopted for the baseline aircraft, which is the F-16. Moreover, contrary to what is mostly done in the literature, the aircraft control surfaces are treated as independent from each other, as they are in the real world. This means that the system is handled as an over-actuated aircraft, and the six degrees of freedom nonlinear flight dynamic model is constructed as an over-actuated system. Over-actuated systems have control effector distribution such that one specific degree of freedom can be stimulated by more than one control surface. As a consequence, such systems require a control allocation approach to distribute control commands over the control effectors. There are several methods in the literature, but an optimization-based control allocation scheme is utilized to satisfy more than one objective: satisfying control moments required with minimum control effort and minimum drag to increase maneuver performance and avoid control surface saturation. However, the main contribution of the study is loss of control prevention. Operating within the flight envelope does not guarantee flight stability. This means that the aircraft may perform a maneuver within the flight envelope, but the corresponding maneuver may stimulate an unstable behavior. Therefore, the aircraft should perform a maneuver inside the dynamic envelope, not the flight envelope, to ensure flight stability. Consequently, the Lyapunov stability theorem-based control moment redesign and dynamic pilot command saturation methods are proposed to ensure flight stability. Furthermore, an incremental attainable moment set method is proposed to generate controllability boundaries of the aircraft in the next step by using the actuator rate and position limits. The aircraft is allowed to use 90\% of its control authority, and an excessive control moment demand is detected using an incremental attainable moment set. After detecting the control authority violation, Lyapunov-based moment regeneration is activated to obtain the maximum possible control inputs, including the angle of attack, velocity vector bank angle and roll rate. Finally, the recalculated maximum possible angle of attack, velocity vector bank angle and roll rate are fed into the pilot demand saturation. In this way, the pilot is restricted from violating the maximum reachable commands in-flight and dynamically, preventing the loss of control and sustaining the safe and stable maneuver. The paramount importance of this study is to prevent the loss of control without intensive computation or \emph{a priori} knowledge of the aircraft. A broad and high-fidelity aerodynamic model alone is sufficient to achieve each step of the proposal as aforementioned. According to the conclusions presented, the proposed method is quite promising. The aircraft's stable behavior can be maintained even under harsh, excessive, and abrupt maneuver requests.