• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 제36회 하계학술대회 논문집 D
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• pp.2537-2539
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• 2005

In many cases the systems are so complex that it is not possible to obtain reasonable models using physical laws. Also a model based on physical laws contains a number of unknown parameters even if the structure is derived from physical laws. These problems can be solved by system identification. In this paper, a nano stage system is selected as an example for system identification. The transfer functions of this system is derived by using state-space model structure based on input/output data through experiment.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.250-255
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• 1993

In this paper, for detection and isolation of instrument and process faults related with steam generator(S/G) in nuclear power plant, two types of observers are designed based on the linearized dynamic model of S/G : a bank of Dedicated Observers (DOS) for instrument faults detection and a bank of Unknown Input Observers(UIO) for process faults detection. And then, they are combined to decide which one between the above two faults occurs. In principle, the failure in ith instrument(process) can be isolated by monitoring the error between the ith output and its estimation obtained from the ith DOS(UIO). It is shown via computer simulations that the present scheme is feasible in finding out the source of a fault.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.499-502
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• 1996

In this paper, we propose a fuzzy iterative learning controller(FILC). It can control fully unknown dynamic plants through iterative learning. To design learning controllers based on the steepest descent method, it is one of the difficult problems to identify the change of plant output with respect to the change of control input(.part.e/.part.u). To solve this problem, we propose a method as follows: first, calculate .part.e/.part.u using a similarity measure and information in consecutive time steps, then adjust the fuzzy logic controller(FLC) using the sign of .part.e/.part..u. As learning process is iterated, the value of .part.e/.part.u is reinforced. Proposed FILC has the simple architecture compared with previous other controllers. Computer simulations for an inverted pendulum system were conducted to verify the performance of the proposed FILC.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.1008-1011
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• 1996

Most control systems of power plants are using classical PID controllers for their process control. In order to get the desired control performances, the correct tuning of PID controllers is very important. Sometimes, it is necessary to retune PID controllers after the change of system operating condition and system design change, etc. Commercial auto-tuning controllers such as relay feedback controller can be used for this purpose. However, using these controllers to the safety-critical systems of nuclear power plants may be cause of unsafe operation, because they are using test signals for tuning. A new system identification auto-tuning method without using test signal has been developed in this paper. This method uses process input/output signals for system identification of unknown control process. From the model information of control process which was obtained from system identification approach, the optimal PID parameters can be calculated. The method can be used in the safety-critical systems because it is not using test signals during system modeling process.

• Transactions on Control, Automation and Systems Engineering
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• 제3권2호
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• pp.106-110
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• 2001

The external force disturbance is the one of the main causes that deteriorate the performance of the magnetic suspension. Thus, this paper develops a fuzzy estimator for gain scheduling control of magnetic suspension system suffering from the unknown disturbance. The propose fuzzy estimator computes the disturbance injected to the plant the gain scheduled controller generates the corresponding stabilizing control input associated with estimated disturbance. In the simulation results we confirm the novelty of the proposed control scheme comparing with the other method using a feedback linearization.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1020-1024
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• 2005

In this paper, an approach to dynamic systems control is addressed based on exploiting the potential features of the new nonlinear neural oscillator. Neural oscillators have recently enabled robots to exhibit natural dynamics using their robustness and entrainment properties. To technically accomplish this objective, the neural oscillator should be connected to the robot joints under the sensory feedback. This also requires the neural oscillator to adapt to the non-periodic nature of arbitrary input patterns. However, even in the most widely-used Matsuoka oscillator, when an unknown quasi-periodic or non-periodic signal is applied, its output signal is not always closely entrained. Therefore, current neural oscillators may not be applied to the precise control of the dynamic systems response. We illustrate the enhanced entrainment properties of the new neural oscillator by numerical simulation and show the possibility for implementation to control a variety of dynamic systems. It is verified that the oscillator can produce rhythmic signals for generating actuator signals which can be naturally modified by incorporating sensory feedback to adapt to outer circumstances.

• The Journal of the Acoustical Society of Korea
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• 제15권4E호
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• pp.21-27
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• 1996

In this paper, we propose a discriminative training algorithm for the stochastic segment model (SSM) in continuous speech recognition. As the SSM is usually trained by maximum likelihood estimation (MLE), a discriminative training algorithm is required to improve the recognition performance. Since the SSM does not assume the conditional independence of observation sequence as is done in hidden Markov models (HMMs), the search space for decoding an unknown input utterance is increased considerably. To reduce the computational complexity and starch space amount in an iterative training algorithm for discriminative SSMs, a hybrid architecture of SSMs and HMMs is programming using HMMs. Given the segment boundaries, the parameters of the SSM are discriminatively trained by the minimum error classification criterion based on a generalized probabilistic descent (GPD) method. With the discriminative training of the SSM, the word error rate is reduced by 17% compared with the MLE-trained SSM in speaker-independent continuous speech recognition.

• 한국컴퓨터정보학회논문지
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• 제4권2호
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• pp.95-104
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• 1999

자동차가 증가함에 따라 교통 안전화를 목적으로 한, 자동차 전반에 관한 연구들이 주요한 과제로 대두되고 있다. 무인화 주행을 위한 시각 시스템은 미리 알려져 있지 않은, 일반적인 도로에서 주행하기 위해서는 연속적으로 입력되는 도로정보로부터 도로정보의 모델을 생성하여 주행에 필요한 도로정보를 추출한다. 본 논문에서는 자동 항법 시스템 중에서 자동 조종에 필요한 도로정보 표지판의 추출 방법을 하프변환과 유전자 알고리즘을 이용하여 제안하고자 한다.

• 한국통신학회논문지
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• 제24권8B호
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• pp.1500-1505
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• 1999

본 논문은 3물체 인식을 위한 깊이정보의 추출을 위해 스테레오 기법의 적용과 기존의 방법론에서 정합횟수에 대한 문제점을 보완하기 위한 물체의 진행 방향 벡터를 이용하는 방법론을 제안한다. 즉, 물체의 진행 방향을 이용하여 진행방향 벡터를 구하고 이를 축으로 회전 이동된 물체를 정합 시킨다. 그리고 Hough변환을 이용하여 얻은 회전 이동에 대응하는 2차원 합성영상을 참조영상으로 설정하고 입력영상과 정합 과정을 수행하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 B
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• pp.683-685
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• 1999

As a method of obtaining pulse transfer function. transfer function of discrete-time from input-output data, there are method of obtaining unknown parameter of pulse transfer function from estimated impulse response before(1-3). There is no need to approximate to several meanings because of not being established algebraical relations between impulse response for estimation error and parameter of transfer function exactly. In this paper, I inquire the method[4] of obtaining the optimal pulse transfer function as a meaning of Hankel norm approximation from impulse response data and examine estimated property as computer simulation from this method.