• 대한전기학회:학술대회논문집
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• 대한전기학회 1991년도 하계학술대회 논문집
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• pp.699-702
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• 1991

A servo system requires faster and more accurate dynamic responses. Generally a PD control is mainly used to obtain the precision, and in the other hand a fuzzy control to improve the transient response and to cope with the nonlinearity of systems. Recently hybrid control, which is attempted to combine the advantages of PD control and a Fuzzy control was proposed, but this technique requires complicate design procedures. Therefore in this paper, a Fuzzy controller with a series of membership functions, and various sampling periods and rules, was designed on the basis of Lyapunov stability theory and auto tuning methods of input scale factors. And also it was showed to have the excellent adaptive performances against internal-external disturbances and the usefulness of this controller from the results of simulations.

• 한국자동차공학회논문집
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• 제21권6호
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• pp.209-217
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• 2013

This paper presents a control strategy of 4 wheel drive (4WD) vehicles. Proposed control strategy has simple structure and can easily apply to various vehicles with low cost and time. It is consist of feedforward control for traction ability, fedback control for minimizing the wheel speed difference and yaw control for lateral stability. In addition, to integrate the traction and stability control, a blending function is applied. To evaluate the feasibility of the proposed control strategy, actual vehicle experiment is conducted after deciding the tuning parameter through the simulation. The simulation is accomplished by CarSim and Matlab/Simulink and the actual vehicle test is conducted using full size Sports Utility Vehicle (SUV) equipped rear wheel based solenoid type 4WD device.

• 한국안전학회지
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• 제8권3호
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• pp.3-12
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• 1993

In reciprocating internal combustion engine, engine performance Is greatly affected by volumetric efficiency. For gas flow, the dynamic effects caused by the pressure pulsation have influence on the volumetric efficiency and correlate to the configuration and pipe length of intake-exhaust system. In this study, the analytic investigation of the unstudy flow In exhaust pipe has been carried out by using the method of characteristics to predict volumetric efficiency. In conculusion, it is possible to take account of the exhaust pipe tuning effect in predicting the engine performance, by the analytic solution of the unsteady flow in the pipes, and comparision of prediction with experimental datas show a good agreement on the pressure varision in the exhaust pipe which has Influence on the volumetric efficiency and performance of engine.

• Structural Engineering and Mechanics
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• 제53권5호
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• pp.847-865
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• 2015

This paper presents the application of a recently developed meta-heuristic algorithm, called Colliding Bodies Optimization (CBO), for size and topology optimization of steel trusses. This method is based on the one-dimensional collisions between two bodies, where each agent solution is considered as a body. The performance of the proposed algorithm is investigated through four benchmark trusses for minimum weight with static and dynamic constraints. A comparison of the numerical results of the CBO with those of other available algorithms indicates that the proposed technique is capable of locating promising solutions using lesser or identical computational effort, with no need for internal parameter tuning.

• 조명전기설비학회논문지
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• 제27권8호
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• pp.75-82
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• 2013

We propose a fiber grating sensor system for condition monitoring of large scale wind turbine blades. For the feasibility test of the proposed sensor system, a down-scaled wind turbine has been constructed and experimented. Fiber grating sensors were attached on a blade surface for distributed strain and temperature measurements. An optical rotary joint was used to transmit optical signals between the FBG sensor array and the signal processing unit. Instead of broadband light source, we used a wavelength-swept fiber laser to obtain high output power density. A spectrometer demodulation is used to alleviate the nonlinear wavelength tuning problem of the laser source. With the proposed sensor system we could measure dynamic strain and temperature profiles at multi-positions of rotating wind turbine blades.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1987년도 전기.전자공학 학술대회 논문집(II)
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• pp.1210-1212
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• 1987

Adaptive control for robot manipulator controller has been considered as an effective approach because robot dynamic models contain the nonlinearities and uncertainties. This paper present an approach for the position and velocity control of a manipulator by using the seif-tuning type controller for each point. The complicated model manipulator system is modeled by a set of time series difference equation. The parameters of the models are determined by online recursive algorithms. Finally some remarks on the effectiveness and applications of adaptive controller are discussed.

• 대한전기학회논문지
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• 제35권5호
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• pp.177-184
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• 1986

An effective cartesian coordinate model is presented to control a robot motion along a prescribed timebased hand trajectory in cartesian coordinates and to provide an adaptive feedback design approach utilizing self-tuning control methods without requiring a detailed mathematical description of the system dynamics. Assuming that each of the hybrid variable set of velocities and forces at the cartesian coordinate level is mutually independent, the dynamic model for the cartesian coordinate control is reduced to first-order SISO models for each degree of freedom of robot hand, including a term to represent all unmodeled effects, by which the number of parameters to be identified is minimized. The self-tuners are designde to minimize a chosen performance criterion, and the computed control forces are resolved into applied joint torques by the Jacobian matrix. The robustness of the model and controller is demonstrated by comparing with the other catesian coordinate controllers.

• Journal of the Optical Society of Korea
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• 제19권1호
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• pp.88-94
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• 2015

This paper reports the fabrication of a lenticular liquid crystal (LC) lens array with thermally tunable focus and with the function of a convertible lens type, using the surface structure of a UV-curable polymer and a twisted-nematic (TN) LC cell. The TN LC cell makes the LC lenticular lens function as a converging or diverging lens by controlling electrically the polarization of input light. Therefore, the focal lengths for both the converging and diverging lenses, which can be switched from the TN cell, can be tuned by changing the effective refractive index of the LC by Joule heating of the transparent electrode. As a result, the focal length of the lens with the E7 LC was changed continuously from 8.7 to 31.2 mm for the converging lens type and from -9.8 to -14.2 mm for the diverging lens when the temperature was increased from 25 to $56^{\circ}C$.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.2552-2556
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• 2005

In general, the forklift driven by DC motor drive system is used in the industrial field. Classically, the DC motor is controlled by current control using proportion control method, by output torque following the load on the plane like a manual operation. But in the industrial field, the forklift is demanded the robust drive mode. Some cases of the mode, there aretrouble in torque control following slope capacity. The control is sensitive concerning about slope angle and output speed, various control method is studied for stability of speed control. In this paper, I apply current control for the self-tuning using the fuzzy controller to obtain robust, stable speed control and use stable, high efficiency control using DSP as main controller for high speed processor, embody dynamic characteristic of control compared the PI controller to the fuzzy controller.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2004년도 추계학술대회 학술발표 논문집 제14권 제2호
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• pp.303-308
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• 2004

Fuzzy logic, neural network, fuzzy-neural network play an important as the key technology of linguistic modeling for intelligent control and decision making in complex systems. The fuzzy-neural network (FNN) learning represents one of the most effective algorithms to build such linguistic models. This paper proposes learning approach of fuzzy-neural network by immune algorithm. The proposed learning model is presented in an immune based fuzzy-neural network (FNN) form which can handle linguistic knowledge by immune algorithm. The learning algorithm of an immune based FNN is composed of two phases. The first phase used to find the initial membership functions of the fuzzy neural network model. In the second phase, a new immune algorithm based optimization is proposed for tuning of membership functions and structure of the proposed model.