• 한국운동역학회지
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• 제13권1호
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• pp.23-38
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• 2003

The purpose of this study is to develop an improved marker auto-identification algorithm for reduce of data processing time through improve the efficiency of noise elimination and marker separation. The maker auto-identification algorithm was programming named KUMAS used Delphi language. For the study, various experiments were conducted for the verification of KUMAS. and compared two systems of established with the KUMAS. Four different motions - cycling, gait, rotation, and pendulum -, were selected and tested. Motions were filmed 30Hz frames rate per second. ${\chi}^2$ used for statistical analysis. Significant level were ${\alpha}=.05$. The test results were as follow. 1. Increased the success ratio of marker auto-identification. 2. The efficiency of marker auto-identification was remarkably improved through marker separation, noise elimination. 3. The marker auto-identification ability was improved in 2D-image plane include the 3D motion. 4. Significant different were found between KUMAS and B-SYS(established system) with non-input the artificial noise frames, input the artificial noise frames and total frames.

• 한국항공우주학회지
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• 제30권7호
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• pp.130-136
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• 2002

본 논문에서는 자동조종장치를 장착한 무인항공기의 시스템 식별을 위한 비행시험기법에 대해 기술하였다. 종운동 및 횡/방향운동 구동입력으로는 멀티스텝 입력을 이용하였다. 각 운동모드에 대해 주파수역 해석을 통해 최적의 입력시간을 설정하였다. 무인항공기의 자동조종장치를 탑재한 비행조종컴퓨터를 이용하여 프로그래밍 모드에서의 비행시험방법으로 종운동과 횡/방향운동의 분리를 통해 시스템 식별을 위한 최적의 자료를 제공하고 있다. 또한 설계치에 근사한 정확한 구동입력을 인가하여 보다 높은 입력주파수를 확보할 수 있었다. 비행시험에서는 안정된 대기상태에서 반복적인 시행을 수행하였으며, 향상된 비행체 탑재 자료저장장치를 이용하여 고품질의 비행자료를 확보하였다. 본 비행시험 기법을 적용하여 획득한 비행자료는 무인항공기의 시스템 식별을 위한 비행자료로 이용되었다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.1711-1716
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• 2004

This paper presents identification and control of a 10-m antenna via accelerometers and angle encoder data. Artificial Neural Networks can be used effectively for the identification and control of nonlinear dynamical system such as a large flexible antenna. Some identification results are shown and compared with the results of conventional prediction error method. And we use a neural network inverse model for control the large flexible antenna. In the neural network inverse model, a neural network is trained, using supervised learning, to develop an inverse model of the antenna. The network input is the process output, and the network output is the corresponding process input. The control results show the validation of the ANN approach for identification and control of the 10-m flexible antenna.

• 한국콘텐츠학회논문지
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• 제15권4호
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• pp.1-8
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• 2015

본 논문에서는 적응적 가중치를 사용한 Least Mean Square Error(LMSE) 최적화 기반의 심전도 개인 인식 방법을 제안하다. 제안하는 방법은 잡음 제거를 위한 전처리과정, 평균 심전도 신호 및 표준편차를 추출한다. 그리고 추출된 정보들을 DB에 저장하고 이를 적응적 가중치로 사용하여 개인 인식에 사용한다. 적응적 가중치는 두 가지를 사용하는데 첫 번째 적응적 가중치는 입력 신호의 표준편차의 역수이고, 두번째 적응적 가중치는 DB에 저장된 사람들의 평균 심전도 신호간의 표준편차에 비례한 것이다. 제안한 방법으로 실험한 결과 32명에 대해서 100%의 인식률을 보였다.

• 디지털콘텐츠학회 논문지
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• 제9권2호
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• pp.165-175
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• 2008

현재 소프트웨어 개발을 위한 방법론은 객체지향에서 컴포넌트지향으로 컴포넌트지향에서 서비스지향 발전되어 오고 있다. 컴포넌트지향 개발 방법과 서비스지향 개발 방법들은 객체지향 UML 모델을 기반으로 분석되어지므로 효율적인 객체지향 분석 방법이 필요하다. 따라서 본 논문에서는 UML 기반의 클래스 식별 및 유스케이스 모델링이 개발자의 직관과 경험에 의존하는 문제점을 보완하여 입력 데이터-처리 프로세스-출력 데이터를 사용한이벤트 기반의 유스케이스 및 클래스 분석 가이드라인과 분석 프로세스를 제안 한다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.485-485
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• 2000

A design method of model following control system using neural networks is proposed. An unknown nonlinear single-input single-output plant is identified using a multilayer neural networks. A linear controller is designed fer the linear approximation model obtained by linearinzing the identification model. The identification model is also used as a plant emulator to obtain the prediction error. Deficient servo performance due to controlling nonlinear plant with only linear controller is mended by adjusting the linear controller output using the prediction output and the parameters of the identification model. An optimal preview controller is adopted as the linear controller by reason of having good servo performance lowering the peak of control input. Validity of proposed method is illustrated through a numerical simulation.

• 설비공학논문집
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• 제3권2호
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• pp.103-113
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• 1991

This paper presents a method for estimating the noise source contribution of a pulse combustion burner in a multiple input system where the input sources may be coherent each other. By coherence function method, it is found that the biggest part of the noise source in the pulse combustion burner is generated by the part of the combustion chamber. This analysis is modeled as three input / single output system because the noise generating mechanism of the pulse combustion burner is very complicated. The coherence function method is proved to be useful tool for the identification of noise source. The overall levels of the radiated source pressure by coherence function method are compared with those measured and calculated by the frequency response function approach. The experimental results have shown a good agreement with the results calculated by the coherence function method when the input sources are coherent strongly each other. The estimation of shield effect by FRF method indicates that significant reduction can be achieved in sound radiation if only transmission path generated by the part of combustion chamber is acoustically shield.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.1412-1415
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• 1996

In this paper, a new identification method of the cascade control system is proposed which can overcome the weak points of Krishnaswamy and Rangaiah(1987)'s method. This new method consists of two steps. One is on-line process identification using the numerical integration to approximate the two process dynamics with a high order linear transfer function. The other is a model reduction technique to derive out low order transfer function(FOPTD or SOPTD) from the obtained high order linear transfer function to tune the controller using usual tuning rules. While the proposed method preserves the advantages of the Krishnaswamy and Rangaiah(1987)'s method, it has such a simplicity that it requires only measured input and output data and simple least-squares technique. Simulation results show that the proposed method can be a promising alternative in the identification of cascade control systems.

• 한국공간구조학회논문집
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• 제3권4호
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• pp.53-58
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• 2003

In order to control seismic responses of building structures effectively and stably, it is very important to estimate the dynamic characteristics of target structure exactly based on input-output signal data. In this paper, it is shown that Subspace Identification Method is able to be applied effectively to system identification of building structures. To verify the efficiency of Subspace Identification Method, the vibration experiments were conducted on a specimen structure which is a 5-storied building structure model consisted of H-shaped steel beam, and the simulated seismic responses of the identified structure model were compared with the observed ones under the same excitation. It was observed that the experimental results coincided with the analyzed ones proposed in this paper.

• 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.