• 대한전기학회:학술대회논문집
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• 대한전기학회 1988년도 전기.전자공학 학술대회 논문집
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• pp.980-985
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• 1988

In this paper, a control system of the PUMA 560 robot manipulator using a PC (Personal Computer) is presented. The hardware of the designed control system is composed of IBM-PC/AT, interface board, selection board, interrupt generating circuit, and the servo control unit of the PUMA controller. A robot control library is developed using assembly and C language, and is composed of several low-level functions and arm interface routines, world model routines, arm kinematics routines, and motion command service routines. Using the designed library, joint interpolated motion and Cartesian interpolated motion of the PUMA robot manipulator are realized. In the future, our system is expected to be a very helpful basis and a useful tool for developing various control algorithms of robot manipulator using sensory information.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2001년도 춘계학술대회논문집B
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• pp.325-329
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• 2001

This paper addresses a control architecture for the hospital service robot, SmartHelper. With a sensing-reasoning-acting paradigm, the deliberation takes place at planning layer while the reaction is dealt through the parallel execution of operations. Hence, the system presents both a hierarchical and an heterarchical decomposition, being able to show a predictable response while keeping rapid reactivity to the dynamic environment. The deliberative controller accomplishes four functions which are path generation, selection of navigation way, command and monitoring. The reactive controller uses fuzzy and potential field method for robot navigation. Through simulation under a virtual environment IGRIP, the effectiveness of the control architecture is verified.

• 한국공간구조학회논문집
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• 제18권4호
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• pp.97-104
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• 2018

A connected control method for the adjacent buildings has been studied to reduce dynamic responses. In these studies, seismic loads were generally used as an excitation. Recently, multi-hazards loads including earthquake and strong wind loads are employed to investigate control performance of various control systems. Accordingly, strong wind load as well as earthquake load was adopted to evaluate control performance of adaptive smart coupling control system against multi-hazard. To this end, an artificial seismic load in the region of strong seismicity and an artificial wind load in the region of strong winds were generated for control performance evaluation of the coupling control system. Artificial seismic and wind excitations were made by SIMQKE and Kaimal spectrum based on ASCE 7-10. As example buildings, two 20-story and 12-story adjacent buildings were used. An MR (magnetorheological) damper was used as an adaptive smart control device to connect adjacent two buildings. In oder to present nonlinear dynamic behavior of MR damper, Bouc-Wen model was employed in this study. After parametric studies on MR damper capacity, optimal command voltages for MR damper on each seismic and wind loads were investigated. Based on numerical analyses, it was shown that the adaptive smart coupling control system proposed in this study can provide very good control performance for Multi-hazards.

• Smart Structures and Systems
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• 제8권1호
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• pp.39-52
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• 2011

We are developing a biomimetic robot based on the Sea Lamprey. The robot consists of a cylindrical electronics bay propelled by an undulatory body axis. Shape memory alloy (SMA) actuators generate propagating flexion waves in five undulatory segments of a polyurethane strip. The behavior of the robot is controlled by an electronic nervous system (ENS) composed of networks of discrete-time map-based neurons and synapses that execute on a digital signal processing chip. Motor neuron action potentials gate power transistors that apply current to the SMA actuators. The ENS consists of a set of segmental central pattern generators (CPGs), modulated by layered command and coordinating neuron networks, that integrate input from exteroceptive sensors including a compass, accelerometers, inclinometers and a short baseline sonar array (SBA). The CPGs instantiate the 3-element hemi-segmental network model established from physiological studies. Anterior and posterior propagating pathways between CPGs mediate intersegmental coordination to generate flexion waves for forward and backward swimming. The command network mediates layered exteroceptive reflexes for homing, primary orientation, and impediment compensation. The SBA allows homing on a sonar beacon by indicating deviations in azimuth and inclination. Inclinometers actuate a bending segment between the hull and undulator to allow climb and dive. Accelerometers can distinguish collisions from impediment to allow compensatory reflexes. Modulatory commands mediate speed control and turning. A SBA communications interface is being developed to allow supervised reactive autonomy.

• 한국컴퓨터정보학회논문지
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• 제26권9호
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• pp.57-64
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• 2021

본 논문에서는 음성 명령을 인식하여 비행기의 1차 조종면을 제어할 수 있는 장치를 제안한다. 음성 명령어는 19개의 명령어로 구성되며 총 2,500개의 데이터셋을 근간으로 학습 모델을 구성한다. 학습 모델은 TensorFlow 기반의 Keras 모델의 Sequential 라이브러리를 이용하여 CNN 모델로 구성되며, 학습에 사용되는 음성 파일은 MFCC 알고리즘을 이용하여 특징을 추출한다. 특징을 인식하기 위한 2단계의 Convolution layer 와 분류를 위한 Fully Connected layer는 2개의 dense 층으로 구성하였다. 검증 데이터셋의 정확도는 98.4%이며 테스트 데이터셋의 성능평가에서는 97.6%의 정확도를 보였다. 또한, 라즈베리 파이 기반의 제어장치를 설계 및 구현하여 동작이 정상적으로 이루어짐을 확인하였다. 향후, 음성인식 자동 비행 및 항공정비 분야의 가상 훈련환경으로 활용될 수 있을 것이다.

• 대한기계학회논문집A
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• 제26권8호
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• pp.1480-1486
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• 2002

In this study, the cross-coupling control (CCC) with three new features is proposed to maintain contour precision in high-speed nonlinear contour machining. One is an improved contour error model that provides almost exact calculation of the errors. Another is the utilization of variable controller gains based on the instantaneous curvature of the contour and the variable command. For this scheme, a stability is analyzed. As a result, the stability region is obtained, and the variable gains are decided within that region. The other scheme in the proposed CCC is a real-time feedrate adaptation module to regulate cutting force fur better surface finish through regulation of material removal rate (MRR). The simulation results show that the proposed CCC system can provide better precision than the existing method particularly in high-speed machining of nonlinear contours.

• 한국군사과학기술학회지
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• 제27권4호
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• pp.437-445
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• 2024

In future complex and diverse battlefield situations, the existing command system faces the challenge of delayed human judgement of strategy and low objectivity. This paper proposes an artificial intelligence model that takes situation information and course of action simulation results as input and automatically assigns scores to various evaluation elements and a comprehensive score. This tool is expected to assist the commander in making decisions, reduce the time required for making judgments, and promote impartial decision-making.

• 제어로봇시스템학회논문지
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• 제10권2호
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• pp.112-124
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• 2004

A neural network based adaptive reconfigurable flight controller is presented for a class of discrete-time nonlinear flight systems in the presence of variations of aerodynamic coefficients and control effectiveness decrease caused by control surface damage. The proposed adaptive nonlinear controller is developed making use of the backstepping technique for the angle of attack, sideslip angle, and bank angle command following without two time separation assumption. Feedforward multilayer neural networks are implemented to guarantee reconfigurability for control surface damage as well as robustness to the aerodynamic uncertainties. The main feature of the proposed controller is that the adaptive controller is developed under the assumption that all of the nonlinear functions of the discrete-time flight system are not known accurately, whereas most previous works on flight system applications even in continuous time assume that only the nonlinear functions of fast dynamics are unknown. Neural networks learn through the recursive weight update rules that are derived from the discrete-time version of Lyapunov control theory. The boundness of the error states and neural networks weight estimation errors is also investigated by the discrete-time Lyapunov derivatives analysis. To show the effectiveness of the proposed control law, the approach is i]lustrated by applying to the nonlinear dynamic model of the high performance aircraft.

• 제어로봇시스템학회논문지
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• 제9권4호
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• pp.329-339
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• 2003

A neural network based adaptive controller design method is proposed for reconfigurable flight control systems in the presence of variations in aerodynamic coefficients or control effectiveness decrease caused by control surface damage. The neural network based adaptive nonlinear controller is developed by making use of the backstepping technique for command following of the angle of attack, sideslip angle, and bank angle. On-line teaming neural networks are implemented to guarantee reconfigurability and robustness to the uncertainties caused by aerodynamic coefficients variations. The main feature of the proposed controller is that the adaptive controller is designed with assumption that not any of the nonlinear functions of the system is known accurately, whereas most of the previous works assume that only some of the nonlinear functions are unknown. Neural networks loam through the weight update rules that are derived from the Lyapunov control theory. The closed-loop stability of the error states is also investigated according to the Lyapunov theory. A nonlinear dynamic model of an F-16 aircraft is used to demonstrate the effectiveness of the proposed control law.

• 정보보호학회논문지
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• 제28권5호
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• pp.1141-1151
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• 2018

APT(Advanced Persistent Threat) 공격에서 감염 호스트와 C&C(Command and Control) 서버 간 통신은 공격 대상의 내부로 침입하기 위한 핵심단계이다. 공격자는 C&C 서버를 통해 다수의 감염 호스트를 제어하고, 침입 및 공격 행위를 지시하는데, 이 단계에서 C&C 서버가 노출되면 공격은 실패할 수 있다. 따라서 최근의 경우 DGA(Domain Generation Algorithm)를 통해 C&C 서버의 DNS를 짧은 시간 간격으로 교체하여 탐지를 어렵게 하고 있다. 특히 하루에도 500만개 이상 새로 등록되는 DNS 전부를 검증하고 탐지하는 것은 매우 어렵다. 이러한 문제점을 해결하기 위해 본 논문에서는 정상 DNS와 DGA를 통해 생성된 DNS(DGA-DNS)의 형태적 유사도(similarity) 분석을 이용한 DGA-DNS 탐지와 이를 통해 APT 공격 징후로 판단하는 모델을 제시하고 유효성을 검증한다.