• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.1127-1128
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• 2008

In this paper, we propose a control method to improve control performance for a Quad-rotor Unmanned Aerial Vehicle's stabilization. The proposed method is the Fuzzy+I control that contains a fuzzy controller which processes signals from the error and the change of error, and generates the control signal by summing up fuzzy output signal and integral signal. We simulated and experimented on the fuzzy+I control method by implementing Quad-rotor UAV that is able to hovering, for the purpose of verifying the effectiveness of the proposed fuzzy+I control method in comparison with general PID control, and we found out that fuzzy+I controller improved control performance of the system.

• Journal of Biosystems Engineering
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• v.35 no.5
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• pp.302-309
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• 2010

Aerial application using an unmanned agricultural helicopter would allow precise and timely spraying. The attitude of a helicopter depends on a number of dynamic variables for roll-balanced flight. Laterally tilting behavior of a helicopter is a physically intrinsic phenomenon while hovering and forwarding. In order to balance the fuselage, the rotor should be counter-tilted, resulting in the biased down-wash. The biased spraying toward right side causes uneven spray pattern. In this study, a raised tail rotor system for the roll-balanced helicopter was studied. Thrust of the tail rotor system was measured and theoretically estimated for the fundamental database of the roll-balanced helicopter design. The estimated tail thrust and roll-moment would be used to design the raising height of tail rotor and roll balancing dynamics. The unmanned agricultural helicopter required the tail rotor thrust of about 39.2 N (4.0 kgf) during hovering with a payload of 235.4 N (24 kgf). A raised tail rotor system would compensate for the physical tilt phenomena. A further attitude control system of helicopter would assist roll-balanced aerial spray application.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.763-766
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• 1996

A model helicopter is an unstable, multi-input multi-output nonlinear system exposed to strong disturbances and its system parameters change continually. In this paper, Time Delay Control(TDC) is adopted for these reasons. TDC uses past observation of the system's response and the control input to directly modify the control action rather than adjusting the controller gains leading to a model independent robust controller. TDC can force the plant to follow an appropriate reference model, but the reference model cannot be chosen arbitrarily. In this paper the procedure of choosing a reference model and the performance of the controller are presented.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1375-1379
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• 2004

Unmanned Helicopter has several abilities such as vertical Take off, hovering, low speed flight at low altitude. Such vehicles are becoming popular in actual applications such as search and rescue, aerial reconnaissance and surveillance. These vehicles also used under risky environments without threatening the life of a pilot. Since a small aerial vehicle is very sensitive to environmental conditions, it is generally known that the flight control is very difficult problems. In this paper, a flight control system was designed for an unmanned helicopter. This paper was concentrated on describing the mechanical design, electronic equipments and their interconnections for acquiring autonomous flight. The design methodologies and performance of the helicopter were illustrated and verified with a linearized equation of motion. The LQG based estimator and controller was designed and tested for this unmanned helicopter.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2079-2081
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• 2002

R/C helicopter has been used to several fields of military affairs, investigation searching and toys because it has small size hovering and vortical take-off characteristics etc. Therefore it needs more realizable control method. The paper introduces simulation and experimental results for control of a helicopter training simulator by self tuning control method. To realize the disturbance rejection and the given reference tracking, a least common multiple polynomial between the reference and disturbance model polynomials is operated to the plant model. The effectiveness of the method is shown by simulation and experimental results for a helicopter training simulator with two degree of freedom.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.210-214
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• 1998

Radio-Controlled helicopter has superior movement abilities like as hovering or backward move. So it has been used as a sprinkler of agricultural medicines or an observer of dangerous area such as a volcano, etc. But its operation is not simple because it has many control factors and they interfere with each other. Therefore the helicopter is not controlled by simple theory in the case of automatic operation. Then fuzzy sliding mode control, which has fastness, fineness and robustness, is thought to be suitable to satisfy various requirements of the helicopter operation. In this work, the fuzzy sliding mode control was applied to the flying of RC helicopter, As tile result, it was controlled with good performance.

• International Journal of Control, Automation, and Systems
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• v.5 no.4
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• pp.364-371
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• 2007

In this paper, we describe the synthesis of robust and non-fragile $H^{\infty}$ state feedback controllers for linear systems with affine parameter uncertainties, as well as a static state feedback controller with poly topic uncertainty. The sufficient condition of controller existence, the design method of robust and non-fragile $H^{\infty}$ static state feedback controller with fuzzy compensator, and the region of controllers that satisfies non-fragility are presented. We show that the resulting controller guarantees the asymptotic stability and disturbance attenuation of the closed loop system in spite of controller gain variations within a resulted polytopic region.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1992.04a
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• pp.173-177
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• 1992

The Helicopter has a lot of flight modes. The most characteristic flight mode is Hovering. It enables the helicopter to be used in many situations. However, a helicopter has nonlinear dynamics so its mathematical modeling is very difficult. Hence it is not easy to control helicopter in hover. In this paper, RC model helicopter is selected as a plant. To stabilize the behavior of RC model helicopter, Fuzzy alogrithm is used as a controller and one camera is used as a sensor. To get proper Information from camera Image, three characteristic points are attatched to the helicopter and a position recognition algorithm is developed. Experiments are performed to stabilize 3 rotational motions synchronousely with fuzzy control algorithm. As a result, Fuzzy control represents better performances than the conventional PID control.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.1
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• pp.26-33
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• 2014

This study addresses the control problem of an unmanned aerial vehicle (UAV) during the transition period when the flying mode changes from hovering to translational motion in the horizontal plane. First, we introduce a compensation algorithm that improves height stabilization and reduces altitude drop. The main principle is to incorporate pitch and roll measurements into the feedforward term of the altitude controller to provide a larger thrust force. To further improve altitude control, we propose the fuzzy logic controller that improves system behavior. Simulation results presented in the paper highlight the effectiveness of the proposed controllers.

• Journal of the Korean Society for Precision Engineering
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• v.30 no.1
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• pp.53-58
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• 2013

In this paper, we present a framework for collision avoidance of UGVs by vision-based control. On the image plane which is created by perspective camera rigidly attached to UAV hovering stationarily, image features of UGVs are to be controlled by our control framework so that they proceed to desired locations while avoiding collision. UGVs are assumed as unicycle wheeled mobile robots with nonholonomic constraint and they follow the image feature's movement on the ground plane with low-level controller. We used potential function method to guarantee collision prevention, and showed its stability. Simulation results are presented to validate capability and stability of the proposed framework.