• Title/Summary/Keyword: on-line identification

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On-line System Identification using State Observer

  • Park, Duck-Gee;Hong, Suk-Kyo
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.2538-2541
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    • 2005
  • This paper deals one of the methods of system identification, especially on-line system identification in time-domain. The algorithm in this study needs all states of the system as well input to it for system identification. In this reason, Kalman filter is used for state estimation. But in order to implement a state estimator, the fact that a system model must be known is logical contradiction. To overcome this, state estimation and system parameter estimation are performed simultaneously in one sample. And the result of the system parameter estimation is used as basis to state estimation in next sample. On-line system identification comes, in every sample by performing both processes of state estimation and parameter estimation that are related mutually and recursively. This paper demonstrates the validity of proposed algorithm through an example of an unstable inverted pendulum system. This algorithm can be useful for on-line system identification of a system that has fewer number of measurable output than system order or number of states.

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Power System State Estimation and Identification in Consideration of Line Switching (선로개폐상태를 포함하는 전력통계 상태추정및 동정)

  • 박영문;유석한
    • 전기의세계
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    • v.28 no.3
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    • pp.57-64
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    • 1979
  • The static state estimation are divided into two groups; estimation and detection & identification. This paper centers on detection and identification algorithm. Especially, the identification of line errors is focused on and is performed by the extended W.L.S. algorithm with line swithching states. Here, line switching states mean the discrete values of line admittance which are influenced by unexpected line switching. The numerical results are obtained from the assumption that the noise vector is independent zero mean Gaussian random variables.

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on-line Modeling of Nonlinear Process Systems using the Adaptive Fuzzy-neural Networks (적응퍼지-뉴럴네트워크를 이용한 비선형 공정의 온-라인 모델링)

  • 오성권;박병준;박춘성
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.48 no.10
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    • pp.1293-1302
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    • 1999
  • In this paper, an on-line process scheme is presented for implementation of a intelligent on-line modeling of nonlinear complex system. The proposed on-line process scheme is composed of FNN-based model algorithm and PLC-based simulator, Here, an adaptive fuzzy-neural networks and HCM(Hard C-Means) clustering method are used as an intelligent identification algorithm for on-line modeling. The adaptive fuzzy-neural networks consists of two distinct modifiable sturctures such as the premise and the consequence part. The parameters of two structures are adapted by a combined hybrid learning algorithm of gradient decent method and least square method. Also we design an interface S/W between PLC(Proguammable Logic Controller) and main PC computer, and construct a monitoring and control simulator for real process system. Accordingly the on-line identification algorithm and interface S/W are used to obtain the on-line FNN model structure and to accomplish the on-line modeling. And using some I/O data gathered partly in the field(plant), computer simulation is carried out to evaluate the performance of FNN model structure generated by the on-line identification algorithm. This simulation results show that the proposed technique can produce the optimal fuzzy model with higher accuracy and feasibility than other works achieved previously.

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Wavelet Neural Network Based Indirect Adaptive Control of Chaotic Nonlinear Systems

  • Choi, Yoon-Ho;Choi, Jong-Tae;Park, Jin-Bae
    • Journal of the Korean Institute of Intelligent Systems
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    • v.14 no.1
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    • pp.118-124
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    • 2004
  • In this paper, we present a indirect adaptive control method using a wavelet neural network (WNN) for the control of chaotic nonlinear systems without precise mathematical models. The proposed indirect adaptive control method includes the off-line identification and on-line control procedure for chaotic nonlinear systems. In the off-line identification procedure, the WNN based identification model identifies the chaotic nonlinear system by using the serial-parallel identification structure and is trained by the gradient-descent method. And, in the on-line control procedure, a WNN controller is designed by using the off-line identification model and is trained by the error back-propagation algorithm. Finally, the effectiveness and feasibility of the proposed control method is demonstrated with applications to the chaotic nonlinear systems.

An Efficient On-line Identification Approach to Rotor Resistance of Induction Motors Without Rotational Transducers

  • Lee, Sang-Hoon;Yoo, Ho-Sun;Ha, In-Joong
    • Journal of Electrical Engineering and information Science
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    • v.3 no.1
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    • pp.86-93
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    • 1998
  • In this paper, we propose an effective on-line identification method for rotor resistance, which is useful in making speed control of induction motors without rotational transducers robust with respect to the variation in rotor resistance. Our identification method for rotor resistance is based on the linearly perturbed equations of the closed-loop system for sensorless speed control about th operating point. Our identification method for rotor resistance uses only the information of stator currents and voltages. In can provide fairly good identification accuracy regardless of load conditions. Some experimental results are presented to demonstrate the practical use of our identification method. For our experimental work, we have built a sensorless control system, in which all algorithms are implemented on a DSP. Our experimental results confirm that our on-line identification method allows for high precision speed control of commercially available induction motors without rotational transducers.

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On-line integration of structural identification/damage detection and structural reliability evaluation of stochastic building structures

  • Lei, Ying;Wang, Longfei;Lu, Lanxin;Xia, Dandan
    • Structural Engineering and Mechanics
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    • v.63 no.6
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    • pp.789-797
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    • 2017
  • Recently, some integrated structural identification/damage detection and reliability evaluation of structures with uncertainties have been proposed. However, these techniques are applicable for off-line synthesis of structural identification and reliability evaluation. In this paper, based on the recursive formulation of the extended Kalman filter, an on-line integration of structural identification/damage detection and reliability evaluation of stochastic building structures is investigated. Structural limit state is expanded by the Taylor series in terms of uncertain variables to obtain the probability density function (PDF). Both structural component reliability with only one limit state function and system reliability with multi-limit state functions are studied. Then, it is extended to adopt the recent extended Kalman filter with unknown input (EKF-UI) proposed by the authors for on-line integration of structural identification/damage detection and structural reliability evaluation of stochastic building structures subject to unknown excitations. Numerical examples are used to demonstrate the proposed method. The evaluated results of structural component reliability and structural system reliability are compared with those by the Monte Carlo simulation to validate the performances of the proposed method.

On-line Identification of fuzzy model using HCM algorithm (HCM을 이용한 퍼지 모델의 On-Line 동정)

  • Park, Ho-Sung;Park, Byoung-Jun;Oh, Sung-Kwun
    • Proceedings of the KIEE Conference
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    • 1999.07g
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    • pp.2929-2931
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    • 1999
  • In this paper, an adaptive fuzzy inference and HCM(Hard C-Means) clustering method are used for on-line fuzzy modeling of nonlinear and complex system. Here HCM clustering method is utilized for determining the initial parameter of membership function of fuzzy premise rules and also avoiding overflow phenomenon during the identification of consequence parameters. To obtain the on-line model structure of fuzzy systems. we use the recursive least square method for the consequent parameter identification. And the proposed on-line identification algorithm is carried out and is evaluated for sewage treatment process system.

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A Reform Measure of the Structure and Transaction Process for the Safety Improvement of a Credit Card (신용카드의 안전성 향상을 위한 구조 및 거래절차 개선방법)

  • Lee, Young Gyo;Ahn, Jeong Hee
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.7 no.3
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    • pp.63-74
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    • 2011
  • Credit cards are more convenient than cash of heavy. Therefore, credit cards are used widely in on_line (internet) and off_line in nowadays. To use credit cards on internet is commonly secure because client identification based security card and authentication certificate. However, to use in off_line as like shop, store, department, restaurant is unsecure because of irregular accident. As client identification is not used in off_line use of credit cards, the irregular use of counterfeit, stolen and lost card have been increasing in number recently. Therefore, client identification is urgently necessary for secure card using in off_line. And the method of client identification must be simple, don't take long time, convenient for client, card affiliate and card company. In this paper, we study a reform measure of the structure and transaction process for the safety improvement of a credit cards. And we propose several authentication method of short-and long-term for client identification. In the proposal, the client authentication method by OTP application of smart-phone is efficient nowadays.

Phase Shift Analysis and Phase Identification for Distribution System with 3-Phase Unbalanced Constant Current Loads

  • Byun, Hee-Jung;Shon, Sugoog
    • Journal of Electrical Engineering and Technology
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    • v.8 no.4
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    • pp.729-736
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    • 2013
  • Power grids are large complicated networks in use around. An absolute phase value for a particular unknown-phase line at a local site should be identified for the operation and management of a 3-phase distribution network. The phase shift for a specific point in the line, as compared with a phase reference point at a substation, must be within a range of ${\pm}60^{\circ}$ for correct identification. However, the phase shift at a particular point can fluctuate depending on the line constants, transformer wiring method, line length, and line amperage, etc. Conducted in this study is a theoretical formulation for the determination of phase at a specific point in the line, Simulink modeling, and analysis for a distribution network. In particular, through evaluating the effects of unbalanced current loads, the limitations of the present phase identification methods are described.

On-line process identification for cascade control system (Cascade 제어를 위한 실시간 공정 식별법)

  • 박흥일;성수환;이인범
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10b
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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.

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