• 제목/요약/키워드: linear processes

검색결과 688건 처리시간 0.023초

Optimal Learning Control Combined with Quality Inferential Control for Batch and Semi-batch Processes

  • Chin, In-Sik;Lee, Kwang-Soon;Park, Jinhoon;Lee, Jay H.
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1999년도 제14차 학술회의논문집
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    • pp.57-60
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    • 1999
  • An optimal control technique designed for simultaneous tracking and quality control for batch processes. The proposed technique is designed by transforming quadratic-criterion based iterative learning control(Q-ILC) into linear quadratic control problem. For real-time quality inferential control, the quality is modeled by linear combination of control input around target qualify and then the relationship between quality and control input can be transformed into time-varying linear state space model. With this state space model, the real-time quality inferential control can be incorporated to LQ control Problem. As a consequence, both the quality variable as well as other controlled variables can progressively reduce their control error as the batch number increases while rejecting real-time disturbances, and finally reach the best achievable states dictated by a quadratic criterion even in case that there is significant model error Also the computational burden is much reduced since the most computation is calculated in off-line. The Proposed control technique is applied to a semi-batch reactor model where series-parallelreactions take place.

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지도학습기법을 이용한 비선형 다변량 공정의 비정상 상태 탐지 (Abnormality Detection to Non-linear Multivariate Process Using Supervised Learning Methods)

  • 손영태;윤덕균
    • 산업공학
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    • 제24권1호
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    • pp.8-14
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    • 2011
  • Principal Component Analysis (PCA) reduces the dimensionality of the process by creating a new set of variables, Principal components (PCs), which attempt to reflect the true underlying process dimension. However, for highly nonlinear processes, this form of monitoring may not be efficient since the process dimensionality can't be represented by a small number of PCs. Examples include the process of semiconductors, pharmaceuticals and chemicals. Nonlinear correlated process variables can be reduced to a set of nonlinear principal components, through the application of Kernel Principal Component Analysis (KPCA). Support Vector Data Description (SVDD) which has roots in a supervised learning theory is a training algorithm based on structural risk minimization. Its control limit does not depend on the distribution, but adapts to the real data. So, in this paper proposes a non-linear process monitoring technique based on supervised learning methods and KPCA. Through simulated examples, it has been shown that the proposed monitoring chart is more effective than $T^2$ chart for nonlinear processes.

해상운임의 구조변화 리스크 추정 (Risk Estimates of Structural Changes in Freight Rates)

  • 김현석
    • 한국항만경제학회지
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    • 제39권4호
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    • pp.255-268
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    • 2023
  • 본 연구는 기존의 비선형 추정에 기초한 구조 단절/변화를 검정하기 위한 모형을 선형 회귀 분석으로 일반화한 모형으로 효율적 추정이 가능함을 제시하고자 한다. 특히, 효율적인 추정을 위해 인공지능, 머신러닝 등 분야와 관련해 구조 단절/변화 모니터링에 대한 관심이 높아지는 최근 이슈에 대해 선형회귀에 근거한 본 연구의 실증분석 결과는 구조 단절을 명확하게 추정하였으며, 글로벌 시황을 나타내는 대표적인 건화물선 운임 지수(발틱 드라이 벌크 지수, BDI)에 대한 적용 결과는 기존 연구와 일치하는 추정 결과를 제시한다. 이상의 선형 회귀에 근거한 분석은 CUSUM, MOSUM, F-통계 기반 프로세스 등 경험적 변동 프로세스의 피팅, 시각화 및 평가를 위한 다양한 유형의 추정에서 통계적으로 유의한 것으로 나타났다. 추가적으로 기존 연구에서 제시한 PELT(pruned exact linear time)를 적용한 추정에서도 유사한 추정 결과를 각각 나타낸다.

A study on the fine structure of marine diatoms in Korean coastal waters: Genus Thalassiosira 5

  • Park, Joon-Sang;Lee, Jin-Hwan
    • ALGAE
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    • 제25권3호
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    • pp.121-131
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    • 2010
  • Thalassiosira species were collected from October 2007 to January 2009 in an attempt to better understand species diversity of the genus Thalassiosira in Korean coastal waters. A total of 5 Thalassiosira species (T. concaviuscula, T. oceanica, T. partheneia, T. simonsenii and T. nanolineata) were identified here. Most species in this study were of small size, and 5 species were recorded for the first time in Korean coastal waters. Using a scanning electron microscope (SEM), we described distinctive characteristics of fine structure that proved to be important diagnostic characteristics for the identification of each species. The most important diagnostic characteristics for Thalassiosira species identification were the marginal strutted processes, the position of labiate processes, and the areolation. The differential characteristics of the species studied were: T. concaviuscula has a double layered external tubes on the marginal strutted processes; T. oceanica shows marginal ridges that are interlinked between the marginal strutted processes; the valve face of T. partheneia is fairly convex and its labiate process is positioned midway between two strutted processes; T. simonsenii is characterized by two labiate processes and somewhat coarse areolae; and, T. nanolineata has several central strutted processes and linear areolation.

A theory of linear quasi-time invariant filters

  • Lee, Heyoung;Bien, Zeungnam
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1996년도 Proceedings of the Korea Automatic Control Conference, 11th (KACC); Pohang, Korea; 24-26 Oct. 1996
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    • pp.362-367
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    • 1996
  • In this paper, the eigenstructure of a class of linear time varying systems, termed as linear quasi-time invariant(LQTI) systems, is investigated. A system composed of dynamic devices such as linear time varying capacitors and resistors can be an example of the class. To effectively describe and analyze the LQTI systems, a generalized differential operator G is introduced. Then the dynamic systems described by the operator G are studied in terms of eigenvalue, frequency characteristics, stability and an extended convolution. Some basic attributes of the operator G are compared with those of the differential operator D. Also the corresponding generalized Laplace transform pair is defined and relevant properties are derived for frequency domain analysis of the systems under consideration. As an application example, a LQTI circuit is examined by using the concept of eigenstructure of LQTI system. The LQTI filter processes the sinusoidal signals modulated by some functions.

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Modeling and Evaluation of Linear Oscillating Actuators

  • Chen, X.;Zhu, Z.Q.
    • Journal of international Conference on Electrical Machines and Systems
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    • 제1권4호
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    • pp.517-524
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    • 2012
  • The operation of linear oscillating system is complicated, involving system nonlinearities of both actuator and load, and variations of driving frequency in order to track the mechanical resonance. In this paper, both analytical and state-variable modeling techniques are used to investigate the influence of actuator parameters, such as back-emf/thrust force coefficient and cogging force, on the performance of linear oscillating systems. Analytical derivations are validated by simulations, and good agreements are achieved. The findings of the paper can greatly facilitate the design and evaluation processes of permanent magnet linear actuators.

High Resolution Linear Graphs : Graphical Aids for Designing Off-Line Process Control)

  • Lee, Sang-Heon
    • 한국국방경영분석학회지
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    • 제27권1호
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    • pp.73-88
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    • 2001
  • Designing high quality products and processes at a low cost is central technological and economic challenge to the engineer. The combination of engineering concepts and statistical implementations offered by Taguchi\`s off-line design technique has proven t be invaluable. By examining some deficiencies in designs from the Taguchi\`s highly fractional, orthogonal main effect plan based on orthogonal arrays, alternative method is proposed. The maximum resolution or the minimum aberration criterion is commonly used for selecting 2$^{n-m}$ fractional designs. We present new high resolution (low aberration) linear graphs to simplify the complexity of selecting designs with desirable statistical properties. The new linear graphs approach shows a substantial improvement over Taguchi\`s linear graphs and other related graphical methods for planning experiment. The new set of linear graphs will allow the experimenter to maintain the simple approach suggested by Taguchi while obtaining the best statistical properties of the resulting design such as minimum aberration as a by-product without dependency on complicated computational algorithm or additional statistical training.g.

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PID 제어를 이용한 파장 스위핑 레이저의 스위핑 선형화 (Sweeping Linearization of Wavelength Swept Laser using PID Control)

  • 엄진섭
    • 센서학회지
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    • 제29권6호
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    • pp.412-419
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    • 2020
  • In this study, a PID control method for sweeping automatic linearization of a wavelength swept laser is proposed. First, the closedloop transfer function embodying the PID control is derived. Through the simulation of the function, Kp = 0.022, Ki = 0.008, Kd = 0.002 were obtained as the best PID coefficients for fast linear sweeping. The performance test using the PID coefficients showed that linear sweeping was held up well with a 98.7% decrement in nonlinearity after the 10th feedback, and 45 nm sweeping range, 1 kHz sweeping frequency, and 8.8 mW average optical power were obtained. The equipment consists of a fiber Bragg grating array, an optical-electronic conversion circuit, and a LabVIEW FPGA program. Every 5s, automatic feedback and PID control generate a new compensated waveform and produce a better linear sweeping than before. Compared with nonlinear sweeping, linear sweeping can reduce the cumbersome and time-consuming recalibration processes and produce more accurate measurement results.

Data Visualization using Linear and Non-linear Dimensionality Reduction Methods

  • Kim, Junsuk;Youn, Joosang
    • 한국컴퓨터정보학회논문지
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    • 제23권12호
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    • pp.21-26
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    • 2018
  • As the large amount of data can be efficiently stored, the methods extracting meaningful features from big data has become important. Especially, the techniques of converting high- to low-dimensional data are crucial for the 'Data visualization'. In this study, principal component analysis (PCA; linear dimensionality reduction technique) and Isomap (non-linear dimensionality reduction technique) are introduced and applied to neural big data obtained by the functional magnetic resonance imaging (fMRI). First, we investigate how much the physical properties of stimuli are maintained after the dimensionality reduction processes. We moreover compared the amount of residual variance to quantitatively compare the amount of information that was not explained. As result, the dimensionality reduction using Isomap contains more information than the principal component analysis. Our results demonstrate that it is necessary to consider not only linear but also nonlinear characteristics in the big data analysis.

Comparison of Titration Curve Estimation Methods for pH Neutralization Processes

  • Park, Ho-Cheol;Lee, Jie-Tae
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2001년도 ICCAS
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    • pp.124.1-124
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    • 2001
  • Control of pH neutralization process plays a very important role in some chemical process. Because of their high nonlinearity, frequent disturbance, and time-varying characteristics, it is difficult to control and estimate pH processes. For the adaptive control of pH processes, a lot of researchers have made an efforts in the modeling and control of pH processes. It is very difficult to obtain information of influent stream such as concentrations and dissociation constants and the titration curve equation is very complex. Therefore, several simple models, which hate small number of unknown parameters and estimate the titration curve, have been available, These models were considered here and were transformed into forms that can applied the linear least square method.

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