• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.04a
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• pp.579-584
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• 2008

A nano-imprinting stage has been widely used in various fields of nanotechnology. In this study, an analysis method of a nano-imprinting stage machine using FEM and flexible multi-body vibration has been presented. The simulation using CAE for the imprinting machine is to analyze vibration characteristics of 3-axis nano-imprinting stage and 4-axis nano-imprinting stage. Structural components such as the upper plate have been modeled with finite elements to analyze flexibility effects during the precision stage motion. In this paper flexible multi-body dynamic simulation is executed to support robust design of the precision stage mechanism.

• The Journal of the Acoustical Society of Korea
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• v.16 no.3E
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• pp.14-18
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• 1997

One fo the major problems in speech recognition is the mismatch between training and testing environments. Recently, SNR normalization technique, which normalizes the dynamic range of frequency channels in mel-scaled filterbank, was proposed[1]. While it showed improved robustness against additive noise, it requires a reliable speech detection mechanism and several adaptation parameters to be optimized. In this paper, we propose a modified SNR normalization technique. In this technique, we take simply the maximum of filterbank output and predetermined masking constant for each frequency band. According to the speaker-independent isolated word recognition in car noise environments, proposed modification yields better recognition performance that the original SNR normalization method, with rather reduced complexity.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.05a
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• pp.587-592
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• 2004

Direct velocity feedback (DVFB) control is known that it offers an unconditional stability with very high performance when the control strategy is applied at a point collocated sensor and actuator pair, because the sensor-actuator pair has strictly positive real (SPR) property. In this paper, two types of collocated sensor-actuator pairs are considered for practical active vibration control of a structure. They are a point collocated sensor-actuator pair and a point sensor-distributed actuator pair. Both pairs with DVFB sho robust stability and performance. It is noted that the collocated point sensor-actuator ultimately acts as a 'skyhook' damper, but the point sensor-distributed actuator pair with DVFB acts as a 'skyhook' rotational dmaper pair.ational dmaper pair.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.05a
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• pp.233-236
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• 2004

In this paper, a new sensorless vibration control scheme is proposed for a flexible manipulator system. A robust sliding mode controller incorporating with a ‘reaction moment observer’ used for the estimation of the reaction moment reciprocally acting on flexible arm and hub inertia is introduced to achieve desired control target. The rigid body dynamics of the single-link flexible manipulator is simply considered in the design of the sliding mode controller. Then, the reaction moment is estimated by the proposed reaction moment observer to suppress the residual vibration of the flexible arm. The performance of the proposed control scheme is verified by computer simulation and experiment.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.06a
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• pp.251-256
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• 2000

This paper presents dynamic modeling and controller design of a tracked vehicle installed with the double-rod type ERSU(electro-rheological suspension unit). A 16 DOF(degree-of-freedom) model for the tracked vehicle is established by Lagrangian method. After showing the spring and damping characteristics of the proposed ERSU, equivalent 2 DOF 1/12 tracked vehicle model is then formulated by regarding the spring and viscous damping coefficients under the static state as constant values. A robust LSDP(loop-shaping design procedure) $H_{\infty}$ controller compensating spring and damping parameter variations is then designed in order to suppress unwanted vibration of the vehicle. The control responses such as vertical and pitch acceleration are presented in time domain.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.06a
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• pp.1204-1209
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• 2000

Many analytical and experimental studies on the active suppression of nonlinear panel flutter by using piezoceramic patch have been carried out. However, these active control methods have a few important problems; a large amount of power is required to operate actuators, and additional apparatuses such as sensor systems and controller are needed. In this study passive suppression schemes for nonlinear flutter of composite panel, which is believed to be more robust suppression system than active control in practical operation, are proposed by using piezoelectric inductor-resistor series shunt circuit. Toward the end, a finite element equation of motion for an electromechanically coupled system is proposed using the Hamilton's principle. To achieve the best damping effect, optimal shape and location of the piezoceramic(PZT) patches are determined by using genetic algorithms. The results clearly demonstrate that the passive damping scheme by using piezoelectric shunt circuit can effectively attenuate the flutter.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.7
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• pp.650-658
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• 2012

This paper proposes a high performance position controller for a driving system using a time optimal controller which has been widely used to control driving systems to achieve desired reference position or velocity in a minimum response time. The main purpose of this research lies in an improvement of transient response performance rather than that of steady-state response in comparison with other control strategies. In order to refine the scheme of time optimal control, Lyapunov stability proofs are incorporated in a controller of standard second order system model. This scheme is applied to the control of a driving system. In view of the simulation and experiment results, the standard second order system model exhibits better minimum-time control performance and robustness than double integral system model does.

• IEMEK Journal of Embedded Systems and Applications
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• v.5 no.2
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• pp.57-66
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• 2010

In this paper, we propose an enhanced voice recognition algorithm using adaptive MFCC(Mel Frequency Cepstral Coefficients) and neural network. Though it is very important to extract voice data from the raw data to enhance the voice recognition ratio, conventional algorithms are subject to deteriorating voice data when they eliminate noise within special frequency band. Differently from the conventional MFCC, the proposed algorithm imposed bigger weights to some specified frequency regions and unoverlapped filterbank to enhance the recognition ratio without deteriorating voice data. In simulation results, the proposed algorithm shows better performance comparing with MFCC since it is robust to variation of the environment.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.54-56
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• 2006

To get the robust and reliable input command, we designed shaping function for target tracking system with commander's handle. Input signals of the commander's handle are generated by human operator. It is response of the human to reduce the error between target and gun. But, tracking error while operator aim a moving target manually gives poor system performance. Input noise, particularly, affects hit accuracy as the system performance. We proposed the design method of input command shaping to reduce the Input noise and to improve the operation ability and convenience. We performed the experiments with combat vehicle, example of Target Tracking System, to show the proposed method is efficient and practical.

• Proceedings of the KIEE Conference
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• 1995.11a
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• pp.161-164
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• 1995

This paper introduces an identification model called the Dynamic Neural Network(DNN) with a multilayer neural network in the forward path and a linear dynamical system in the feedback path, and defines Dynamic BackPropagation(DBP) as a learning algorithm for it. This identification model uses the feedback of its own output as a learning signal, which is not affected by a noise added to the output terminal of the plant so, it can be considered as a parallel identification model, and when compared with a series-parallel model which does not use the concept of the feedback, the proposed identification scheme exhibits more robust performance.