• Convergence Security Journal
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• 제23권2호
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• pp.103-113
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• 2023

In recent years, Unmanned Aerial Vehicles (UAV) have been widely used in various industries. However, as the depend ence on UAV increases rapidly, concerns about the security and safety of UAV are growing. Currently, various vulnerabili ties such as stealing the control right of the UAV or the right to communicate with the UAV in the web application are being disclosed. However, there is a lack of research related to the security of UAV. Therefore, in this paper, a study was conducted to determine whether the packet data was normal or abnormal by collecting packet data of an unmanned aerial vehicle in a HITL(Hardware In The Loop) simulation environment similar to the real environment. In addition, this paper proposes a method for reducing computational cost in the modeling process and increasing the ease of data interpretation, a machine learning-based anomaly detection model that detects abnormal data by learning only normal data, and optimized hyperparameter values.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• 제36권6호
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• pp.565-573
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• 2008

The behavior-based decentralized approach is considered for multi-UAV formation flight. It is assumed that each UAV has its own mission of flying to a specified region, while the distances between UAVs should be maintained. These two requirements may conflict with each other. To design the controller, coupled dynamics approach is applied to multi-UAVs with an assumption that each UAV can communicate with each other to share the state-information. Control gain matrices are optimized to acquire better performances of formation flying. To validate the proposed control approach, numerical simulation is performed for the waypoint-passing mission of multi-UAVs.

• KIPS Transactions on Software and Data Engineering
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• 제6권9호
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• pp.429-436
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• 2017

Unmanned Aerial Vehicles (UAV) that are piloted without human pilots can be commanded remotely via frequencies or perform pre-inputted missions. UAVs have been mainly used for military purposes, but due to the development of ICT technology, they are now widely used in the private sector. Teal Group's 2014 World UAV Forecast predicts that the UAV market will grow by 10% annually over the next decade, reaching $ 12.5 billion by 2023. However, because UAVs are primarily remotely controlled, if a malicious user accesses a remotely controlled UAV, it could seriously infringe privacy and cause financial loss or even loss of life. To solve this problem, a secure channel must be established through mutual authentication between the UAV and the control center. However, existing security techniques require a lot of computing resources and power, and because communication distances, infrastructure, and data flow are different from UAV networks, it is unsuitable for application in UAV environments. To resolve this problem, the study presents a lightweight UAV authentication method based on Physical Unclonable Functions (PUFs) that requires less computing resources in the ground Control and Non-Payload Communication (CNPC) environment, where recently, technology standardization is actively under progress.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• 제38권4호
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• pp.352-362
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• 2010

The simultaneous operation of multiple UAV's makes it possible to enhance the mission accomplishment efficiency. In order to achieve this, easily scalable control algorithms are required, and swarm intelligence having such characteristics as flexibility, robustness, decentralized control, and self-organization based on behavioral model comes into the spotlight as a practical substitute. Recently, evolutionary robotics is applied to the control of UAV's to overcome the weakness of difficulties in the logical design of behavioral rules. In this paper, a neural network controller evolved by evolutionary robotics is applied to the control of multiple UAV's which have the mission of searching limited area. Several numerical demonstrations show the proposed algorithm has superior results to those of behavior based neural network controller which is designed by intuition.

• International Journal of Control, Automation, and Systems
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• 제4권6호
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• pp.782-787
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• 2006

The role of Unmanned Aircraft Vehicles(UAVs) has been increasing significantly in both military and civilian operations. Many complex systems, such as UAVs, are difficult to model accurately because they exhibit nonlinearity and show variations with time. Therefore, the control system must address the issues of uncertainty, nonlinearity, and complexity. Hence, identification of the mathematical model is an important process in controller design. In this paper, attitude dynamics identification of UAV is investigated. Using the flight data, nonlinear state space model for attitude dynamics of UAV is derived and verified. Real time simulation results show that the model dynamics match experimental data.

• Journal of Institute of Control, Robotics and Systems
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• 제13권10호
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• pp.927-932
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• 2007

The sophisticated mathematical model is required for the design and the database construction of the advanced flight control system of UAV. In this paper, flight test of KARI's research UAV, often called DURUMI-II, is implemented for the data acquisition from the maneuver flight. The flight path reconstruction is implemented to ensure that the measured data is consistent and error free. The nonlinear system identification for the refined mathematical modeling is implemented with the verified measurements from the flight path reconstruction. The simulation with the identified results have a good validation when the simulated responses were compared to the flight tested data.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 한국소음진동공학회 2008년도 추계학술대회논문집
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• pp.743-748
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• 2008

This paper presents an inertia type of piezostack based active mount for unmanned aero vehicle (UAV) camera system. After identifying the stiffness and damping properties of the rubber element and piezostack a mechanical model of the active mount system is established. The governing equation of mount is them derived and expressed in a state space farm. Subsequently, a sliding mode controller which is robust to uncertain parameters is designed in order to reduce the vibration imposed according to the military specification associated with UAV camera mount system operation. Control performances such as acceleration and transmitted force are evaluated through both computer simulation and experimental implementation.

• International Journal of Aeronautical and Space Sciences
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• 제7권2호
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• pp.145-154
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• 2006

Many kinds of unmanned aerial vehicles (UAVs) have been developed for a few decades and some of them are now in operational use. Although each UAV as well as a piloted aircraft might have restrictions to execute some tasks simultaneously or to carry some payloads, one with an automatic chase aircraft might have the potential of multi-capabilities to conduct a variety of missions or to carry more storages. This paper introduces a chase UAV control system to enhance a leader (reference) aircraft capability which has storage restriction. The automatic chase guidance and control system will be introduced with the pure pursuit guidance law combined with relative velocity error corrections, and a dynamic inversion technique in order to generate the guidance forces.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• 제18권12호
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• pp.1278-1285
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• 2008

This paper presents an inertia type of piezostack based active mount fur unmanned aero vehicle (UAV) camera system. After identifying the stiffness and damping properties of the rubber element and piezostack a mechanical model of the active mount system is established. The governing equation of mount is then derived and expressed in a state space form. Subsequently, a sliding mode controller which is robust to uncertain parameters is designed in order to reduce the vibration imposed according to the military specification associated with UAV camera mount system operation. Control performances such as acceleration and transmitted force are evaluated through both computer simulation and experimental implementation.

• ETRI Journal
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• 제45권5호
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• pp.811-821
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• 2023

We propose an adaptive unmanned aerial vehicle (UAV)-assisted object recognition algorithm for urban surveillance scenarios. For UAV-assisted surveillance, UAVs are equipped with learning-based object recognition models and can collect surveillance image data. However, owing to the limitations of UAVs regarding power and computational resources, adaptive control must be performed accordingly. Therefore, we introduce a self-adaptive control strategy to maximize the time-averaged recognition performance subject to stability through a formulation based on Lyapunov optimization. Results from performance evaluations on real-world data demonstrate that the proposed algorithm achieves the desired performance improvements.