• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1994년도 Proceedings of the Korea Automatic Control Conference, 9th (KACC) ; Taejeon, Korea; 17-20 Oct. 1994
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• pp.558-560
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• 1994

In this paper, a memoryless H$_{\infty}$ controller for linear systems with state and input delays is presented. The proposed controller is a delay independent stabilizer which reduces the H$_{\infty}$ norm of the closed loop transfer function, from the disturbance to the controlled output, to a precribed level. The controller is obtained by solving a minimization problem involving linear matrix inequalities.s.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 하계학술대회 논문집 D
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• pp.2117-2119
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• 2001

This paper proposes a novel intelligent digital redesign technique for a class of nonlinear systems represented by input-delayed Takagi-Sugeno (TS) fuzzy systems. The digitally redesigned controller can show good performance provided that the analog controller is well-designed. The developed digital redesign technique is based on the 'state-matching', so the control performance is guaranteed as well as the stability of the system. An simulation example is included to ensure the effectiveness of the proposed method.

• 한국정밀공학회지
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• 제13권12호
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• pp.22-29
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• 1996

In this paper the nodes of the multilayer hidden layers have been modified for modeling the nonlinear systems. The structure of nodes in the hidden layers is built with the feedforward, the cross talk and the recurrent connections. The feedforward links are mapping the nonlinear function and the cross talks and the recurent links memorize the dynamics of the system. The cross talks are connected between the modes in the same hidden layers and the recurrent connection has self feedback, and these two connections receive one time delayed input signals. The simplified steam boiler and the analytic multi input multi output nonlinear system which contains process noise have been modeled using this neural networks.

• 대한공업교육학회지
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• 제31권2호
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• pp.364-380
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• 2006

본 연구는 모델링 오차를 갖는 유연구조물의 잔류진동을 억제하는 입력설계에 대한 방법이다. 개루프 제어방법으로 시간지연방법을 이용하여 여러 가지 형태로 설계된 입력을 사용하여 유연구조물의 강체운동과 잔류진동을 억제함을 시뮬레이션과 실험을 통해 비교 확인해 보았다. 또한 모델 오차에 대한 강인성 측면에서도 해석적으로 개루프 시스템에서 검토해 보았다. 여기서 사용된 입력설계(Input-Shaping) 방법은 일련의 임펄스 콘볼류션을 이용하여 진동이 제어되는 입력을 설계한다. 실린더 모양의 허브와 양쪽에 유연한 날개 모양을 가진 모델이 실험에 이용되었으며 제안된 입력설계 명령과 설계되지 않은 명령에 대한 강체운동과 구조물의 잔류진동을 측정하여 입력설계 방법의 효과를 확인하였다. 날개모양의 구조물은 길고 유연하여 운동 상태에서 낮은 주파수 진동을 수반하는 구조물이다. 또한, 적절히 설계된 입력이 폐루프 제어시스템의 입력으로 사용할 때의 응답을 개루프 제어시스템의 응답과 비교하기 위해 해석적 방법을 통해 살펴보았다. 제어의 목적은 강체의 빠른 정착시간, 유연 구조물의 빠른 잔류진동 감쇄, 모델의 불확실성에 대한 강인성 등을 검토해 보는 것이다.

• The Journal of the Acoustical Society of Korea
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• 제23권4E호
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• pp.112-119
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• 2004

This paper presents a method for the automatic recognition of pitch accents with no prior knowledge about the phonetic content of the signal (no knowledge of word or phoneme boundaries or of phoneme labels). The recognition algorithm used in this paper is a time-delay recurrent neural network (TDRNN). A TDRNN is a neural network classier with two different representations of dynamic context: delayed input nodes allow the representation of an explicit trajectory F0(t), while recurrent nodes provide long-term context information that can be used to normalize the input F0 trajectory. Performance of the TDRNN is compared to the performance of a MLP (multi-layer perceptron) and an HMM (Hidden Markov Model) on the same task. The TDRNN shows the correct recognition of $91.9{\%}\;of\;pitch\;events\;and\;91.0{\%}$ of pitch non-events, for an average accuracy of $91.5{\%}$ over both pitch events and non-events. The MLP with contextual input exhibits $85.8{\%},\;85.5{\%},\;and\;85.6{\%}$ recognition accuracy respectively, while the HMM shows the correct recognition of $36.8{\%}\;of\;pitch\;events\;and\;87.3{\%}$ of pitch non-events, for an average accuracy of $62.2{\%}$ over both pitch events and non-events. These results suggest that the TDRNN architecture is useful for the automatic recognition of pitch accents.

• Nuclear Engineering and Technology
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• 제35권5호
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• pp.399-411
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• 2003

A model predictive control method is applied to design an automatic controller for thermal power control in a reactor core. The basic concept of the model predictive control is to solve an optimization problem for a finite future at current time and to implement as the current control input only the first optimal control input among the solutions of the finite time steps. At the next time step, the second optimal control input is not implemented and the procedure to solve the optimization problem is then repeated. The objectives of the proposed model predictive controller are to minimize the difference between the output and the desired output and the variation of the control rod position. The nonlinear PWR plant model (a nonlinear point kinetics equation with six delayed neutron groups and the lumped thermal-hydraulic balance equations) is used to verify the proposed controller of reactor power. And a controller design model used for designing the model predictive controller is obtained by applying a parameter estimation algorithm at an initial stage. From results of numerical simulation to check the controllability of the proposed controller at the $5\%/min$ ramp increase or decrease of a desired load and its $10\%$ step increase or decrease which are design requirements, the performances of this controller are proved to be excellent.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2020년도 학술발표회
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• pp.123-123
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• 2020

The present study is aimed to correcting radar-based mean areal precipitation forecasts to improve urban flood predictions and uncertainty analysis of water levels contributed at each stage in the process. For this reason, a long short-term memory (LSTM) network is used to reproduce three-hour mean areal precipitation (MAP) forecasts from the quantitative precipitation forecasts (QPFs) of the McGill Algorithm for Precipitation nowcasting by Lagrangian Extrapolation (MAPLE). The Gangnam urban catchment located in Seoul, South Korea, was selected as a case study for the purpose. A database was established based on 24 heavy rainfall events, 22 grid points from the MAPLE system and the observed MAP values estimated from five ground rain gauges of KMA Automatic Weather System. The corrected MAP forecasts were input into the developed coupled 1D/2D model to predict water levels and relevant inundation areas. The results indicate the viability of the proposed framework for generating three-hour MAP forecasts and urban flooding predictions. For the analysis uncertainty contributions of the source related to the process, the Bayesian Markov Chain Monte Carlo (MCMC) using delayed rejection and adaptive metropolis algorithm is applied. For this purpose, the uncertainty contributions of the stages such as QPE input, QPF MAP source LSTM-corrected source, and MAP input and the coupled model is discussed.

• 한국정보통신학회논문지
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• 제25권11호
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• pp.1619-1626
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• 2021

증분형 아날로그 디지털 변환기는 전통적인 델타 시그마 아날로그 디지털 컨버터와 달리 리셋 동작을 통한 입력과 출력의 1:1 매핑이 가능하며 이는 멀티플렉싱에 매우 용이하게 사용될 수 있다. 또한, 증분형 아날로그 디지털 변화기는 전통적인 델타 시그마 변환기에 비해 간단한 디지털 필터 설계가 가능하다. 따라서, 본 논문에서는 아날로그 디지털 컨버터 설계에 기본이 되는 딜레이가 있는 적분기와 딜레이가 없는 적분기의 시간 영역에서의 분석을 시작으로 2차 입력 피드 포워드, 확장된 카운팅, 2+1 매쉬, 2+2 매쉬 구조를 갖는 증분형 아날로그 디지털 변환기의 설계 방정식을 유도한다. 이를 통해 설계 이전에 증분형 아날로그 디지털 변환기의 성능을 예측할 수 있을 뿐만 아니라 각각의 아날로그 디지털 변화기에 적합한 디지털 필터를 설계할 수 있다. 또한, 아날로그 디지털 변환기의 정확도를 향상 시키기 위한 확장된 카운팅, MASH의 설계 기술들을 제안하였다.

• 지능정보연구
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• 제5권1호
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• pp.103-123
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• 1999

Input filtering as a preprocessing method is so much crucial to get good performance in time series forecasting. There are a few preprocessing methods (i.e. ARMA outputs as time domain filters, and Fourier transform or wavelet transform as time-frequency domain filters) for handling time series. Specially, the time-frequency domain filters describe the fractal structure of financial markets better than the time domain filters due to theoretically additional frequency information. Therefore, we, first of all, try to describe and analyze specially some issues on the effectiveness of different filtering methods from viewpoint of the performance of a neural network based forecasting. And then we discuss about neural network model architecture issues, for example, what type of neural network learning architecture is selected for our time series forecasting, and what input size should be applied to a model. In this study an input selection problem is limited to a size selection of the lagged input variables. To solve this problem, we simulate on analyzing and comparing a few neural networks having different model architecture and also use an embedding dimension measure as chaotic time series analysis or nonlinear dynamic analysis to reduce the dimensionality (i.e. the size of time delayed input variables) of the models. Throughout our study, experiments for integration methods of joint time-frequency analysis and neural network techniques are applied to a case study of daily Korean won / U. S dollar exchange returns and finally we suggest an integration framework for future research from our experimental results.

• 한국지진공학회논문집
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• 제18권2호
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• pp.89-94
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• 2014

Spatial variations of a seismic wave are mainly wave passage and wave scattering. Wave passage effect is produced by changed characteristics of exciting seismic input motions applied to the bedrock. Modified input motions travel horizontally with time differences determined by apparent shear wave velocity of the bedrock. In this study, wave passage effect on the seismic response of a structure-soil system is investigated by modifying the finite element software of P3DASS (Pseudo 3-Dimensional Dynamic Analysis of a Structure-soil System) to apply inconsistent (time-delayed) seismic input motions along the soft soil-bedrock interface. Study results show that foundation size affected on the seismic response of a structure excited with inconsistent input motions in the lower period range below 0.5 seconds, and seismic responses of a structure were decreased considerably in the lower period range around 0.05 seconds due to the wave passage. Also, shear wave velocity of the bedrock affected on the seismic response of a structure in the lower period range below 0.3 seconds, with significant reduction of the seismic response for smaller shear wave velocity of the bedrock reaching approximately 20% for an apparent shear wave velocity of 1000m/s at a period of 0.05 seconds. Finally, it is concluded that wave passage effect reduces the seismic response of a structure in the lower period range when the bedrock under a soft soil is soft or the bedrock is located very deeply, and wave passage is beneficial for the seismic design of a short period structure like a nuclear container building or a stiff low-rise building.