• Proceedings of the KIEE Conference
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• 2005.07d
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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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• 1993.10a
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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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• 1996.10b
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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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• 1996.10b
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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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• v.3 no.2
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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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• 2005.06a
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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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• v.15 no.4E
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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.

• Journal of the Korea Society of Computer and Information
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• v.4 no.2
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• pp.95-104
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• 1999

With the increasing of cars, general studies of them for the traffic safety have been raised as important problems. Visual system to radio-controled driving is to sample road traffic information as reconstructing a model from lots of road traffic information which is successively input in order to drive on unknown road. This paper proposes a sampling process of the road traffic information board needed in automatic driving under automatic drive system using Hough Transform and Genetic Alorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.8B
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• pp.1500-1505
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• 1999

In this paper, we presented the stereo algorithm for 3-D object recognition. In order to solve the problem for matching time in existed methods, we proposed the method which used the moving direction vector. On the other hand, after we extracted the moving vectors by moving direction of objects, rotated object was matched on axis of it. Using the Hough transform, we obtained the 2-D synthesed image as reference images corresponding to the rate of moving, and then compared with the unknown input images.

• Proceedings of the KIEE Conference
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• 1999.07b
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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.