• 제목/요약/키워드: variable identification

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중학교 과학교육에서 변인통제 능력 향상 프로그램 적용 효과 (The Effect of an Enhancing Program for Variable Control Abilities Applied to the Science Education in Middle School)

  • 김희진;김희수
    • 과학교육연구지
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    • 제36권2호
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    • pp.251-262
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    • 2012
  • 본 연구에서는 중학교 학생들의 변인 판별 및 변인 통제 능력을 신장시킬 수 있는 15가지의 학습 프로그램을 개발하고, 이를 적용하여 수업효과를 분석하였다. 변인 판별 및 통제 학습 효과를 높이기 위하여 자신의 사고 과정을 모니터하고 인지 활동 결과에 대해 객관적으로 평가할 수 있도록 구성하였다. 이 프로그램의 수업 효과를 분석한 결과, 프로그램을 투입한 실험집단이 비교집단에 비해 변인 판별 점수가 높았으며, 변인통제 논리 형성정도도 증가하였는데, 특히 변인통제 논리 형성정도가 미형성 단계인 학생들에게 효과가 크게 나타났다. 이는 우리가 개발한 학습 프로그램을 통해 학생들의 변인 판별 및 통제 능력을 향상시키는 것이 가능함을 보여준다. 또한, 변인 통제 능력 점수와 메타 인지 수준 점수 간에 정(+)적인 상관관계를 보였다. 이는 메타인지 전략이 변인 통제 능력을 유의미하게 향상시키는 효과가 있다고 할 수 있다.

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전기-유압 서보 시스템의 모델규명에 관한 연구 (A Study on Model Identification of Electro-Hydraulic Servo Systems)

  • 엄상오;황이철;박영산
    • 한국정보통신학회논문지
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    • 제3권4호
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    • pp.907-914
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    • 1999
  • This paper studies on the model identification of electro-hydraulic servo systems, which are composed of servo valves, double-rod cylinder and load mass. The identified plant is described as a discrete-time ARX or ARMAX model which is respectively obtained from the identification algorithms of least square error method, instrumental variable method and prediction error method. where a nominal model and the variation of model parameters are quantitatively evaluated.

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Extending the SRIV Identification Algorithm to MIMO LMFD Models

  • Akroum, Mohamed;Hariche, Kamel
    • Journal of Electrical Engineering and Technology
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    • 제4권1호
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    • pp.135-142
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    • 2009
  • In this paper the Simplified Refined Instrumental Variable (SRIV) identification algorithm for SISO systems is extended to MIMO systems described by a Left Matrix Fraction Description (LMFD). The performance of the extended algorithm is compared to the well-known MIMO four-step instrumental variable (IV4) algorithm. Monte Carlo simulations for different signal to noise ratios are conducted to assess the performance of the algorithm. Moreover, the algorithm is applied to a simulated quadruple tank process.

IDENTIFICATION OF SINGLE VARIABLE CONTINUITY LINEAR SYSTEM WITH STABILITY CONSTRAINTS FROM SAMPLES OF INPUT-OUTPUT DATA

  • Huang, Zhao-Qing;Ao, Jian-Feng
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 22-24 Oct. 1991
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    • pp.1883-1887
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    • 1991
  • Identification theory for linear discrete system has been presented by a great many reference, but research works for identification of continuous-time system are less than preceding identification. In fact, a great man), systems for engineering are continuous-time systems, hence, research for identification of continuous-time system has important meaning. This paper offers the following results: 1. Corresponding relations for the parameters of continuous-time model and discrete model may be shown, when single input-output system has general characteristic roots. 2. To do identification of single variable continuity linear system with stability constraints from samples of input-output data, it is necessary to use optimization with stability constraints. 3. Main results of this paper may be explained by a simple example.

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IV 방법을 이용한 잡음이 포함된 베어링 실험 장치의 동특성 파라미터 추출 (An Application of the Instrumental Variable Method(IVM) to a Parameter Identification of a Noise Contaminated Bearing Test Rig)

  • 이용복;김창호;최동훈
    • 소음진동
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    • 제6권5호
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    • pp.679-684
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    • 1996
  • The Instrumental Variable Method(IVM), modified from least square algorithm, is applied to parameter identification of a noise contaminated bearing test rig. The signal to noise ratio included in Frequency Response Function(FRF) can cause significant errors in parameter identification. Therefore, among several candidates of parameter identification method, results of the applied IVM were compared with noise-contaminated least square method. This study shows that the noise-contaminated least square method can have indonsistent accuracy depending on the degree of noise level, while the IVM has robuster performance to signal to noise ratio than least square method.

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A Model Reference Variable Structure Control based on a Neural Network System Identification for an Active Four Wheel Steering System

  • Kim, Hoyong;Park, Yong-Kuk;Lee, Jae-Kon;Lee, Dong-Ryul;Kim, Gi-Dae
    • 한국자동차공학회논문집
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    • 제8권6호
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    • pp.142-155
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    • 2000
  • A MIMO model reference control scheme incorporating the variable structure theory for a vehicle four wheel steering system(4WS) is proposed and evaluated for a class of continuous-time nonlinear dynamics with known or unknown uncertainties. The scheme employs an neural network to identify the plant systems, where the neural network estimates the nonlinear dynamics of the plant. By the Lyapunov direct method, the algorithm is proven to be globally stable, with tracking errors converging to the neighborhood of zero. The merits of this scheme is that the global system stability is guaranteed and it is not necessary to know the exact structure of the system. With the resulting identification model which contains the neural networks, it does not need higher degrees of freedom vehicle model than 3 degree of freedom model. Th proposed scheme is applied to the active four wheel system and shows the validity is used to investigate vehicle handing performances. In simulation of the J-turn maneuver, the reduction of yaw rate overshoot of a typical mid-size car improved by 30% compared to a two wheel steering system(2WS) case, resulting that the proposed scheme gives faster yaw rate response and smaller side angle than the 2WS case.

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Vehicle Face Re-identification Based on Nonnegative Matrix Factorization with Time Difference Constraint

  • Ma, Na;Wen, Tingxin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제15권6호
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    • pp.2098-2114
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    • 2021
  • Light intensity variation is one of the key factors which affect the accuracy of vehicle face re-identification, so in order to improve the robustness of vehicle face features to light intensity variation, a Nonnegative Matrix Factorization model with the constraint of image acquisition time difference is proposed. First, the original features vectors of all pairs of positive samples which are used for training are placed in two original feature matrices respectively, where the same columns of the two matrices represent the same vehicle; Then, the new features obtained after decomposition are divided into stable and variable features proportionally, where the constraints of intra-class similarity and inter-class difference are imposed on the stable feature, and the constraint of image acquisition time difference is imposed on the variable feature; At last, vehicle face matching is achieved through calculating the cosine distance of stable features. Experimental results show that the average False Reject Rate and the average False Accept Rate of the proposed algorithm can be reduced to 0.14 and 0.11 respectively on five different datasets, and even sometimes under the large difference of light intensities, the vehicle face image can be still recognized accurately, which verifies that the extracted features have good robustness to light variation.

드릴링 작업의 모델링과 진단법에 관한 연구 (A Study on the Modeling and Diagnostics in Drilling Operation)

  • 윤문철
    • 동력기계공학회지
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    • 제2권2호
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    • pp.73-80
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    • 1998
  • The identification of drilling joint dynamics which consists of drilling and structural dynamics and the on-line time series detection of malfunction process is substantial not only for the investigation of the static and dynamic characteristics but also for the analytic realization of diagnostic and control systems in drilling. Therefore, We have discussed on the comparative assessment of two recursive time series modeling algorithms that can represent the drilling operation and detect the abnormal geometric behaviors in precision roundshape machining such as turning, drilling and boring in precision diemaking. For this purpose, simulation and experimental work were performed to show the malfunctional behaviors for drilling operation. For this purpose, a new two recursive approach (Recursive Extended Instrument Variable Method : REIVM, Recursive Least Square Method : RLSM) may be adopted for the on-line system identification and monitoring of a malfunction behavior of drilling process, such as chipping, wear, chatter and hole lobe waviness.

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쓰레기 소각플랜트의 상태공간모델 규명에 관한 연구 (A Study on Identification of State-Space Model for Refuse Incineration Plant)

  • 황이철;전충환;이진걸
    • 대한기계학회논문집B
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    • 제24권3호
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    • pp.354-362
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    • 2000
  • This paper identifies a discrete-time linear combustion model of Refuse Incineration Plant(RIP) which characterizes steam generation quantity, where the RIP is considered as a MIMO system with thirteen-inputs and one-output. The structure of RIP model is described as an ARX model which are analytically obtained from the combustion dynamics. Furthermore, using the Instrumental Variable(IV) identification algorithm, model structure and unknown parameters are identified from experimental input-output data sets, In result, it is shown that the identified ARX model well approximates the input-output combustion characteristics given by experimental data sets.

기준모델 적응방식에 개선된 보조변수를 사용한 유도전동기 속도제어 (Speed Control of Induction Motor Using Improved Auxiliary Variable in Model Reference Adaptive System)

  • 서영수;백동현;송호빈;이범용
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1998년도 하계학술대회 논문집 F
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    • pp.2008-2011
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    • 1998
  • When the vector control, which does not need a speed signal from a mechanical speed sensor, it is possible to reduce the cost of the control equipment and to improve the control performance in many industrial application. This paper describes a rotor speed identification method of induction motor based on the theory of Model Reference Adaptive System(MRAS). The identifier execute the rotor speed identification so that the vector control of the induc-tion motor may be achieved. The improved auxiliary variable are introduce to perform accurate rotor speed identification. Simulation and experimental result show the validity of the proposed control method.

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