• International Journal of Internet, Broadcasting and Communication
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• 제8권1호
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• pp.1-6
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• 2016

Keeping a system in stable state is one of the important issues of control theory. The main goal of our basic research is stability of unmanned aerial vehicle (quadrotor). This type of system uses a variety of sensors to stabilize. In control theory and automatic control system to stabilize any system it is need to apply feedback control based on information from sensors. Our aim is to provide balance based on the 3D spatial information in real time. We used PID control method for stabilization of a seesaw balancing system and the article presents our experimental results. This paper presents the possibility of balancing of seesaw system based on feedback information from stereo vision system only.

• 한국항행학회논문지
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• 제20권4호
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• pp.298-304
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• 2016

본 논문은 초음파 거리계를 이용하는 쿼드로터 무인항공기의 고도 제어 성능 향상을 위한 웨이블릿 패킷 변환 기법을 제시하였다. 쿼드로터의 수직 이착륙 시 많이 사용되는 초음파 거리계를 이용하여 지상시험을 수행하였다. 초음파 거리계는 정반사율 (specular reflectance)과 음향 잡음 (acoustic noise)으로 인한 신호의 스파이크가 생긴다. 짧은 시간 간격으로 발생하는 스파이크는 시간과 주파수 영역에서의 동시 분석을 필요로 한다. 이에 초음파 거리계의 스파이크를 웨이블릿 패킷 변환을 이용하여 분석하였다. DWT (discrete wavelet transform)에 비해 웨이블릿 패킷 분해가 더 풍부한 시간-주파수 국소 정보를 얻을 수 있어 초음파 신호의 스파이크를 분석하고 처리하기에 더 효과적이다. 실험결과 초음파 거리계의 스파이크를 효과적으로 제거할 수 있음을 확인하였다.

• 제어로봇시스템학회논문지
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• 제20권4호
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• pp.381-388
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• 2014

In this paper, the attitude of a quadrotor system is controlled by a time-delayed control method which uses the previous information to cancel out uncertainties in the system. Although the linear controller works for the attitude control, the robust performance against disturbance is relatively poor. Therefore, a time-delayed controller as a robust controller is used. Experimental studies are conducted to validate the performance by the time-delayed control method. The performances of both a linear controller and a time-delayed controller are compared.

• International Journal of Aeronautical and Space Sciences
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• 제10권2호
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• pp.148-160
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• 2009

By the development of recent technology, a new variant of rotorcrafts having four rotors start drawing attention from aerial-robotics engineers more than before. Its potential spans from just being control device test bed to performing difficult task such as carrying surveillance device to unreachable places. In this regards, modeling a quad-rotor is significant in analyzing its dynamic behavior and in synthesizing control system for such a vehicle. This paper summarizes the modeling of a mini quad-rotor aerial vehicle. A first principle approach is considered for deriving the model based on Euler-Newton equations of motion. The result of the modeling is a simulation platform that is expected to acceptably predict the dynamic behavior of the quad-rotor in various flight conditions. Linear models associated with different flight condition can be extracted for the purpose of control synthesis.

• 한국정밀공학회지
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• 제33권6호
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• pp.499-508
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• 2016

This paper describes a study of performance prediction of an electric propulsion system for multirotor UAVs. The electric propulsion system consists of motors, propellers, batteries and speed controllers, and significantly affects performance characteristics of the platform. The performance of the electric propulsion system for multirotor UAVs was predicted using an analytical model derived from the characteristics of each component, operation experiments and statistical analyses. Ground performance tests and endurance flights were performed to verify the reliability of the proposed performance prediction method. A quadrotor platform was designed to demonstrate the parcel delivery service used in the endurance flight. From the result of verification tests, it was confirmed that the proposed method has a good agreement.

• 한국인터넷방송통신학회논문지
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• 제12권6호
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• pp.141-146
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• 2012

본 논문에서는 영상 기반 자동 착륙 시스템 개발과 이 시스템을 사용하는 멀티로터 플랫폼 개발에 대해서 소개 한다. 멀티로터 플랫폼은 뉴턴 오일러 개념을 근간으로 하는 강체 운동 모델링을 하였고, LQR 제어 기법을 통한 제어기 튜닝 및 시뮬레이션을 하였다. 영상기반 자동 착륙 시스템은 멀터로터 시스템에 탑재된 단일 카메라를 사용하여 추가적인 임무장비 없이 증강 현실 알고리즘을 사용하여 마커를 탐지하고 정밀한 착륙을 유도하도록 GCS와 연동 코드를 구현 하였다.

• 전기학회논문지
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• 제66권7호
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• pp.1123-1130
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• 2017

This paper deals with the dynamic surface control based tracking control for a drone equipped with a 2-DOF manipulator. First, the dynamics of drone and 2-DOF manipulator are derived separately. And we obtain the combined model of a drone equipped with a manipulator considering the inertia and the reactive torque generated by a manipulator. Second, a dynamic surface control based attitude and altitude control method is presented. Also, multiple sliding mode control based position control method is presented. The system stability and convergence of tracking errors are proven using Lyapunov stability theory. Finally, the simulation results are given to verify the effectiveness of the proposed control method.

• International Journal of Aeronautical and Space Sciences
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• 제18권3호
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• pp.588-600
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• 2017

We develop a wireless, contact free power transfer mechanism that is safer than the direct metallic contact and robust to imperfect alignment on landing at the base station. A magnetic field is created using inductors on both the transmitting and receiving sides. We use the inductive wireless recharging to increase autonomy and decrease the sensor interference by reducing the inductor loop size. By locating four independent small receiver loops and corresponding four circuits around the quadrotor UAV, we can increase safety from circuit malfunctions in comparison to the use of just one loop. On the base station, four folding robotic bars are used to realign the receiver loops over the transmitter loops. After adequate recharging as measured by battery voltages or power consumption at the bae station, the UAV sends a signal to the base station to open the robotic bars and takes off once freed from the robotic bars.

• 로봇학회논문지
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• 제17권1호
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• pp.76-85
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• 2022

One of the most fundamental challenges when designing controllers for dynamic systems is the adjustment of controller parameters. Usually the system model is used to get the initial controller, but eventually the controller parameters must be manually adjusted in the real system to achieve the best performance. To avoid this manual tuning step, data-driven methods such as machine learning were used. Recently, reinforcement learning became one alternative of this problem to be considered as an agent learns policies in large state space with trial-and-error Markov Decision Process (MDP) which is widely used in the field of robotics. However, on initial training step, as an agent tries to explore to the new state space with random action and acts directly on the controller parameters in real systems, MDP can lead the system safety-critical system failures. Therefore, the issue of 'safe exploration' became important. In this paper we meet 'safe exploration' condition with Control Barrier Function (CBF) which converts direct constraints on the state space to the implicit constraint of the control inputs. Given an initial low-performance controller, it automatically optimizes the parameters of the control law while ensuring safety by the CBF so that the agent can learn how to predict and control unknown and often stochastic environments. Simulation results on a quadrotor UAV indicate that the proposed method can safely optimize controller parameters quickly and automatically.

• International Journal of Aeronautical and Space Sciences
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• 제14권2호
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• pp.172-182
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• 2013

This paper focuses on the modeling and intelligent control of the new Eight-Rotor MAV, which is used to solve the problem of the low coefficient proportion between lift and gravity for the Quadrotor MAV. The Eight-Rotor MAV is a nonlinear plant, so that it is difficult to obtain stable control, due to uncertainties. The purpose of this paper is to propose a robust, stable attitude control strategy for the Eight-Rotor MAV, to accommodate system uncertainties, variations, and external disturbances. First, an interval type-II fuzzy neural network is employed to approximate the nonlinearity function and uncertainty functions in the dynamic model of the Eight-Rotor MAV. Then, the parameters of the interval type-II fuzzy neural network and gain of sliding mode control can be tuned on-line by adaptive laws based on the Lyapunov synthesis approach, and the Lyapunov stability theorem has been used to testify the asymptotic stability of the closed-loop system. The validity of the proposed control method has been verified in the Eight-Rotor MAV through real-time experiments. The experimental results show that the performance of the interval type-II fuzzy neural network based adaptive sliding mode controller could guarantee the Eight-Rotor MAV control system good performances under uncertainties, variations, and external disturbances. This controller is significantly improved, compared with the conventional adaptive sliding mode controller, and the type-I fuzzy neural network based sliding mode controller.