• 한국통신학회논문지
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• 제15권4호
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• pp.295-300
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• 1990

역 운동학 문제는 로보트 매니퓰레이터 제어에서 중요한 관점이 되어 왔다. 본 논문에서는 Jacobi 제어 기법을 실현하기 위하여 Hopfield, Tank의 신경회로망 모델을 사용하였다. 뉴런의 상태는 매니퓰레이터의 관절 속도를 나타내고, 연결강도는 Jacobi 행렬의 값으로 결정되어 진다. 회로망의 에너지 함수는 실제 관절 속도와 원하는 관절 속도간의 최소 자승 오차와 대응하도록 구성한다. 매 샘플링에서 연결 강도와 뉴런의 상태는 현재의 관절위치값에 따라서 변한다. 여유 자유도를 가지는 평면 매니퓰레이터에 대한 역 운동학 해를 컴퓨터 시뮬레이션을 통하여 구하였다.

• 대한전기학회논문지
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• 제39권1호
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• pp.92-106
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• 1990

Active compliance is often used in the control of robot manipulators for the implementation of complex tasks such as assembly, multi-finger fine motion, legged-vehicle adaptive control,etc. This technique balances the interactive force between the manipulator tip and its working environment with its position and velocity errors to achieve the operation of a damped spring. This paper investigates the effecft of passive compliance on system stability with regard to force feedback implementation for actively compliant motion. Usually it is understood that accurate position control require a stiff system. However, theoretical examination of control experiments on a legged suspension vehicle suggests that, if the control includes discrete-time force feedback, some passive compliance is necessssary at the legs of the vehicle for system stability. This can be an important factor to bl considered in manipulator design and control. A theoretical analysis, numerical simulation, and experimental result, confirming the above conclusion, are introduced in this paper.

• 한국통신학회논문지
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• 제38C권9호
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• pp.775-780
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• 2013

Localization, or positioning, is gaining the increasing attention of researchers around the world. The location information, especially the indoor location, is important for navigation systems, heating and air conditioning systems, illumination adjustment, humidity control, robot service, and so on. In this paper, we propose a three-dimensional indoor localization technique using visible light. The main goal of our proposed scheme is to improve the accuracy of VLC-based indoor localization by utilizing multiple VLC transmitters. The simulation results validate the performance of our proposed scheme.

• 한국해양공학회지
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• 제14권2호
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• pp.7-12
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• 2000

This paper presents a non-regressor based adaptive control scheme for the trajectory tracking of underwater vehicle-mounted manipulator systems(UVMS). The adaptive control system includes a class of unmodeled effects is applied to the trajectory control of an UVMS. The only information required to implement this scheme ios the upper bound and lowe bound of the system parameter matrices the upper bound of unmodeled effects the number of joints the position and attitude of the vehicle and trajectory commands. The adaptive control law estimates control gains defined by the combinations of the bounded constants of system parameter matrices and of a filtered error equation. To evaluate the performance of the non-regressor based adaptive controller computer simulation was performed with a two-link planar robot model mounted on an underwater vehicle. The hydrodynamic effects acting on the manipulator are included. It is assumed that the vehicle's motion is slow and can be predicted with a proper compensator.

• 전기학회논문지
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• 제58권9호
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• pp.1827-1833
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• 2009

This paper deals with the trajectory tracking control of wheeled mobile robots with input constraint. The proposed method converts the trajectory tracking problem to the system stability problem using the control inputs composed of feedforward and feedback terms, and then, by using Taylor series, nonlinear terms in origin system are transformed into polynomial equations. The composed system model can make it possible to obtain the control inputs using numerical tool named as SOSTOOL. From the simulation results, the mobile robot can track the reference trajectory well and can have faster convergence rate of the trajectory errors than the existing nonlinear control method. By using the proposed method, we can easily obtain the control input for nonlinear systems with input constraint.

• Journal of Electrical Engineering and Technology
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• 제7권6호
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• pp.845-851
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• 2012

Power system loads have a significant impact on a system. Although it is difficult to precisely describe loads in a mathematical model, accurately modeling them is important for a system analysis. The traditional load modeling method is based on the load components of a bus. Recently, the load modeling method based on measurements from a system has been introduced and developed by researchers. The two major components of a load modeling problem are determining the mathematical model for the target system and estimating the parameters of the determined model. We use the composite load model, which has both static and dynamic load characteristics. The ZIP model and the induction motor model are used for the static and dynamic load models, respectively. In this work, we propose the measurement-based parameter estimation method for the composite load model. The test system and related measurements are obtained using transient security assessment tool(TSAT) simulation program and PSS/E. The parameter estimation is then verified using these measurements. Cases are tested and verified using the sample system and its related measurements.

• 대한산업공학회지
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• 제21권2호
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• pp.239-254
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• 1995

Automated Storage/Retrieval (AS/R) systems have been used mostly in manufacturing or distribution industry in order to store or retrieve palletized items automatically. Since the items ore heavy or bulky, only one pallet at a time is moved by the stacker crane In this study, however, we introduce the "multi -load" AS/R system in which the items to be stored are data storage devices of equal size such as video tape or compact disc. Since the items are small and light multiple items can be stored and retrieved in each trip by using a magazine and a robot arm mounted on the crane Given the magazine capacity, and the locations of retrieval items and empty cells in the rack, the throughput of the multi-load AS/R system will depend on the selection of storage locations and the sequence of visits. We propose four heuristic algorithms for the multi-command. Computer simulation is used to evaluate the four algorithms in terms of throughput and number of back tracking of the crane.

• 한국군사과학기술학회지
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• 제21권2호
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• pp.204-210
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• 2018

As the 4th industrial revolution and artificial intelligence technology develop, it is expected that there will be a revolutionary changes in the security robot. However, artificial intelligence system requires enormous hardwares for tremendous computing loads, and there are many challenges that need to be addressed more technologically. This paper introduces precise tracking control technique of autonomous system that need to move repetitive paths for security purpose. The input feedforward signal is generated by using the inverse based iterative learning control theory for the 2 input 2 output nonminimum-phase system which was difficult to overcome by the conventional feedback control system. The simulation results of the input signal generation and precision tracking of given path corresponding to the repetition rate of extreme, such as bandwidth of the system, shows the efficacy of suggested techniques and possibility to be used in military security purposes.

• Journal of information and communication convergence engineering
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• 제17권4호
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• pp.255-260
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• 2019

A pendubot is a representative example of an underactuated system that has fewer actuators than the degree of freedom of the system. In this study, the characteristics of the pendubot are first reviewed; each part is then designed using Solidworks by dividing the pendubot into three parts: the base frame, first link frame, and second link frame. These three parts are then imported into the Simulink environment via a STEP file format, which is the standard protocol used in data exchange between CAD applications. A 3D model of the pendubot is then constructed using Simscape, and the usefulness of the 3D model is validated by a comparison with a dynamic equation derived using the Lagrangian formulation. A linearized model around an upright equilibrium position is finally obtained, and a sliding mode controller is designed based on the linear quadratic regulator. Simulation results showed that the designed controller effectively maintained upright balance of the pendubot in the presence of disturbance.

• 대한전기학회논문지
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• 제43권5호
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• pp.838-847
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• 1994

Although there is an analytical proof of modeling capability of the neural network, the convergency error in nonlinearity modeling is inevitable, since the steepest descent based practical larning algorithms do not guarantee the convergency of modeling error. Therefore, it is difficult to apply the neural network to control system in critical environments under an on-line learning scheme. Although the convergency of modeling error of a neural network is not guatranteed in the practical learning algorithms, the convergency, or boundedness of tracking error of the control system can be achieved if a proper feedback control law is combined with the neural network model to solve the problem of modeling error. In this paper, the neural network is introduced for compensating a system uncertainty to control a nonlinear dynamic system. And for suppressing inevitable modeling error of the neural network, an iterative neural network learning control algorithm is proposed as a virtual on-line realization of the Adaptive Variable Structure Controller. The efficiency of the proposed control scheme is verified from computer simulation on dynamics control of a 2 link robot manipulator.