• Journal of Advanced Navigation Technology
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• v.14 no.5
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• pp.596-603
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• 2010

This paper presents a homing guidance law of anti-ship missiles using flight path angle to achieve an impact time constraint as well as an impact angle constraint. the independent variable in the nonlinear engagement model is change d from the flight time to the heading angle of the missile. The proposed guidance law can home a missile to the target with zero miss distance as well as satisfying both of the impact angle and time constraints. The performance of the proposed guidance law is evaluated by the computer simulations.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.12
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• pp.1039-1047
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• 2017

This paper presents a test development of a Fly-By-Wireless flight control system for a fixed-wing unmanned aerial vehicle (UAV). Fly-By-Wireless system (FBWLS) refers to a system that uses a wireless network instead of a wired network to connect sensors and actuators with a flight control computer (FCC), reducing considerable amount of wires. FBWLS enables to design a much lighter aircraft along with decreased maintenance time and cost. In this research we developed a Zigbee-based FWBLS UAV in which sensors (GPS and AHRS) are wirelessly connected via a FCC to aileron and elevator servo motors. In order to see the effect of time delay due to wireless signal on the flight stability of the UAV, several flight tests were conducted. From the tests, it was confirmed that the effect is minor by comparing the flight response of the FBWLS with the corresponding Fly-By-Wire system.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.2
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• pp.168-173
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• 2015

The flight control of aircraft, which has nonlinear time-varying dynamic characteristics depending on the various and unexpected external conditions, can be performed on two motions: longitudinal motion and lateral motion. In the longitudinal motion control of aircraft, pitch and trust are major control parameters and roll and yaw are control ones in the lateral motion control. Until now, a number of efficient and reliable control schemes that can guarantee the stability and maneuverability of the aircraft have been developed. Recently, the intelligent flight control scheme, which differs from the conventional control strategy requiring the various and complicate procedures such as the wind tunnel and environmental experiments, has attracted attention. In this paper, an intelligent longitudinal control scheme has been proposed utilizing Interval Type-2 fuzzy logic which can be recognized as a representative intelligent control methodology. The results will be verified through computer simulation with a F-4 jet fighter.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2546-2548
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• 2005

본 논문에서는 무인항공기의 비행제어시스템 개발 및 성능분석을 위한 HILS(Hardware-in-the-Loop-Simulation) 시스템의 구축을 제안한다. 제안한 HILS 시스템은 실시간 시뮬레이션 컴퓨터(dSPACE DS1005), 3축 모션테이블, 자세 센서, 지상통제장치(GCS; Ground Control Station), 비행제어컴퓨터(FCC; Flight Control Computer)로 구성된다. 실제 신호와 유사한 신호를 발생시키기 위한 실시간 시뮬레이션 컴퓨터는 dSPACE가 담당하며, 이 신호는 비행운동을 재현을 위한 3축 모션테이블을 동작시키게 된다. 모션테이블 상에 위치하는 자세센서 값과 GCS의 명령은 FCC의 입력으로 사용된다. 구현된 HILS 시스템을 이용하여 UAV의 제어알고리즘 및 자세센서 성능 검증을 수행하였다.

• Journal of Korea Multimedia Society
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• v.20 no.6
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• pp.927-934
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• 2017

As the technology of drone develops, the use of drone is increasing, In addition, the types of sensors that are inside of smart phones are becoming various and the accuracy is enhancing day by day. Various of researches are being progressed. Therefore, we need to control drone by using smart phone's sensors. In this paper, we propose the most suitable machine learning model that matches the gyro sensor data with drone's moving. First, we classified drone by it's moving of the gyro sensor value of 4 and 8 degree of freedom. After that, we made it to study machine learning. For the method of machine learning, we applied the One-Rule, Neural Network, Decision Tree, and Navie Bayesian. According to the result of experiment that we designated the value from gyro sensor as the attribute, we had the 97.3 percent of highest accuracy that came out from Naive Bayesian method using 2 attributes in 4 degree of freedom. On and the same, in 8 degree of freedom, Naive Bayesian method using 2 attributes showed the highest accuracy of 93.1 percent.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.2
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• pp.354-361
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• 2018

This paper describe the Lateral Navigation algorithm design and verification that implementation on Mission Computer's OFP for Korean Utility Helicopter(KUH) instead of Auto Flight Control System(AFCS) Vehicle Management System. The LNAV function transmits Roll command into the AFCS System. The Roll command value will be calculated by control algorithms in MC. The Operational Flight Program(OFP) shall use for its calculations different measurements of the aircraft's attitude and place. Using these inputs, the OFP will translate a navigational demand(for example-to perform the selected flight plan) into Roll commands to the autopilot. By conducting integration test using SIL and ground test, flight test, it is confirmed that the introduced algorithm meets the requirements of the Mission Equipment Package(MEP) system. LNAV function is verified through the System Integration Laboratory(SIL) test, ground and flight test.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.5
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• pp.479-486
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• 2013

There exist two major difficulties in developing flight control system: nonlinear dynamic characteristics and time-varying properties of parameters of aircraft. Instead of the difficulties, many high reliable and efficient control methodologies have been developed. But, most of the developed control systems are based on the exact mathematical modelling of aircraft and, in the absence of such a model, it is very difficult to derive performance, robustness and nominal stability. From these aspects, recently, some approaches to utilizing the intelligent control theories such as fuzzy logic control, neural network and genetic algorithm have appeared. In this paper, one advanced intelligent lateral control system of a high speed fight has been developed utilizing type-2 fuzzy logic, which can deduce the uncertainty problem of the conventional fuzzy logic. The results will be verified through computer simulation.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.12
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• pp.1209-1216
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• 2009

This paper presents the pose estimation of a small UAV utilizing visual information from low cost cameras installed indoor. To overcome the limitation of the outside flight experiment, the indoor flight test environment based on multi-camera systems is proposed. Computer vision algorithms for the proposed system include camera calibration, color marker detection, and pose estimation. The well-known extended Kalman filter is used to obtain an accurate position and pose estimation for the small UAV. This paper finishes with several experiment results illustrating the performance and properties of the proposed vision-based indoor flight test environment.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.2
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• pp.140-147
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• 2017

This paper describes the design and implementation of previously developed PMU (Power Monitoring Unit) for LiPB (Lithium-ion Polymer Battery) that is electric propulsion used as unmanned aerial vehicle's power source. Improved PMU provides stable voltage and current to various sensors and elctric motors necessary during flight. Voltage and current monitoring function that is measured by improved PMU more precisely be enhanced and the monitoring channel and temperature sensor is added. To verify the improved performance of the equipment, it is integrated to electric propulsion system of unmanned aerial vehicle. PMU is calibrated through the ground test. And PMU's performance is checked through the flight test.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.6
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• pp.73-79
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• 2009

For the shake of control for movement object, control theory like neural network, nonlinear model predictive control(NMPC) is realized on digital high speed computer. Predictor of flight control system(FCS) based nonlinear model predictive control has to be satisfied with response for hard real-time to perform applications on each module in the FCS. Simultaneously, It gives a serious consideration accuracy to give full play to FCS's performance. Error of mathematical aspect affects realization of whole algorithm. But factors of bring mathematical error is not considered to calculate final accuracy on parameter of predictor. In this paper, Predictor was made using load control model on the digital computer for design FCS at hard real-time and is shown response time on realization algorithm. And is shown realization algorithm of high effective predictor over the accuracy. The predictor was realized on the load control model using Euler method, Heun method, Runge-Kutta and Taylor method.