• 전기학회논문지
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• 제59권10호
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• pp.1894-1899
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• 2010

This note is concerned with a robust sliding mode control(SMC) for a class of unmatched uncertain system with severe commensurate state time delay. The suggested method is extended to the control of severe state time delay systems with unmatched uncertainties except the matched input matrix uncertainty. A transformed sliding surface is proposed and a stabilizing control input is suggested. The closed loop stability together with the existence condition of the sliding mode on the proposed sliding surface is investigated through one Lemma and two Theorems by using the Lyapunov direct method with the concept of the control Lyapunov function instead of complex Lyapunov-Kravoskii functionals. Through an illustrative example and simulation study, the usefulness of the main results is verified.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2002년도 전력전자학술대회 논문집
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• pp.415-418
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• 2002

In the paper, a four-phase 16/12 structure Switched Reluctance motor drive is presented. The construction of the stator and the rotor in the motor, the scheme of the rotor position detector and the main circuit of the power converter are described. The comparison of the four-phase 16/12 motor and the four-phase 816 motor and the comparison of the four-phase 16/12 motor and the three-phase 12/8 motor are made. In the controller, the PWM control variable-speed control, the commutation control, the four quadrants control, the overvoltage protection, the overcurrent protection and the under voltage protection could be achieved. Tested results of the developed prototype are made.

• 한국항공운항학회지
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• 제15권3호
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• pp.24-32
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• 2007

In this research, using Terfenol-D actuator composed of magnetostrictive material as shaker and controller, active vibration control theory was applied and verified by experiments. PPF(positive Position Feedback) algorithm which is effective for the control of low frequency vibration was used for the control of a structure. Responses of inputs due to various design variable used for the PPF filter were observed. To investigate the characteristics of magnetostrictive materials, actuator responses were measured for known inputs and satisfactory results were obtained to reduce the vibration level after applying the control input for the actuator.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2018년도 전력전자학술대회
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• pp.454-455
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• 2018

The impedance of an underwater acoustic transducers constituting a multi-channel array structure could be changed in real time by various transmission modes. A power amplifier for driving the transducers usually use a voltage control method, so the transducer and power amplifier may be damaged by over-power due to changeable load conditions. Therefore, the drive controller of the power amplifier should have the function of limiting the power. This paper propose the new voltage control method for limiting the driving power of transducers with variable impedance characteristics.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 D
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• pp.3013-3015
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• 2000

The stabilization control of Inverted Pendulum(IP) system is difficult because of its nonlinearity and structural unstability. Futhermore, a series of conventional techniques such as the pole placement and the optimal control based on the local linearizations have narrow stabilizable regions, At the same time, the fine tunings of their gain parameters are also troublesome, Thus, in this paper, an Evolving Neural Network ControlleY(ENNC) which its structure and its connection weights are optimized simultaneously by Real Variable Elitist Genetic Algorithm (RVEGA) was presented for stabilization of an IP system with nonlinearity, This proposed ENNC was described by a simple genetic chromosome. Through the simulation and experimental results, we showed that the finally acquired optimal ENNC was very useful in the stabilization control of IP system.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 D
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• pp.2455-2457
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• 2000

In this paper, it is proposed a neural adaptve control algorithm for boiler-turbine system. Control inputs are constructed using RBF Neural networks and variable structure inputs are added to improve the robustness. This proposed algorithm does not need the information about parameters and can assure the robustness under the output disturbance and parameter perturbations. The results of computer simulations is presented to verify the efficiency of the proposed algorithm.

• 한국생산제조학회지
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• 제21권1호
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• pp.109-115
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• 2012

In this paper, we consider the sway suppression control problem for container cranes with load hoisting. The proposed control law improves the positioning accuracy but also the sway suppression through fast stabilization of the under-actuated sway dynamics, which is based on a class of feedback linearizing control incorporated with an additional control including the sway angle and its rate as well as positioning errors and their rates. For the design of the additional control, a variable structure control with the proper sway damping and simple switching action is employed, thus preventing excessive overshoots of the trolley travelljng and effectively suppressing the residual sway of container arrived at the target position. Simulation results are provided to show effectiveness of the proposed controller in the presence of such uncertainties as winds and the variation of payload weights.

• 한국지능시스템학회논문지
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• 제11권1호
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• pp.9-15
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• 2001

브러쉬 없는 직류전동기의 위치제어를 위한 퍼지가변구조제어기를 설계한다. 특히 본 논문에서는 기존의 퍼지제어 기법에서 얻을 수 있는 특징으로부터 하나의 전건부 변수만을 가지는 간단한 퍼지논리제어기의 설계를 기술한다. 가변구조제어는 시스템의 파라메터 변화나 외란에 둔감한 특성을 갖는다. 하지만 리칭페이스에서는 문제가 된다. 이를 개선하기 위하여 본 논문에서는 지수항을 추가한 비선형 슬라이딩면을 구성한다. 그리고 나서 비선형 슬라이딩 면과 슬라이딩 면의 변화율을 입력으로 하는 퍼지 제어기를 설계한다. 이러한 2-입력 퍼지가변구조제어기의 제어 규칙표로부터 하나의 전건부 변수만을 가지는 단일 입력 퍼지가변구조제어기를 설계한다. 이들 제어기의 성능을 입증하기 위하여 시뮬레이션과 실험을 수행한다.

• 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.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1993년도 하계학술대회 논문집 A
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• pp.380-382
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• 1993

In this paper, we derive a simple robust nonlinear control scheme for n-link robot manipulators subject to parameter uncertainty. By using the theory of variable structure system(VSS) and taking advantage of the important property of the robot dynamics, the stability of the derived control scheme is proved. This scheme utilizes the desired trajectory outputs, which can be calculated a priori, instead of the actual joint outputs in the nonlinear compensation controller. So the amount of on-line calculations is largely reduced, and as a result, this scheme can be implemented much more efficiently.