• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 추계학술대회 논문집 전기기기 및 에너지변환시스템부문
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• pp.313-316
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• 2002

In this paper, we present an online scheme for parameter estimation of solar cell, based on the model adjustment technique and a genetic algorithm. The ideal diode model and the diode model with series and shunt resistor are used to estimate their parameters. Simulation works using field data in the form of a VI characteristic curve are carried out to demonstrate the effectiveness of the proposed method.

• 전기학회논문지P
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• 제58권4호
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• pp.385-390
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• 2009

This paper presents a novel active noise control (ANC) system using least mean square (LMS) algorithm and neural network approach for decreasing acoustic noise signals inside high-speed trains. We construct a LMS framework as a nominal ANC system and additionally design an artificial single-layered perceptron model as an auxiliary ANC which is aimed to reduce real-time residuary noise due to its nonstationary and uncertain nature. Parameter vector of the hybrid ANC is determined through online estimation to realize an adaptive ANC configuration by means of the steepest descent algorithm. We achieve simulation experiment to demonstrate the proposed ANC system employing realistic acoustic noise signals measured in Korea Train eXpress (KTX).

• Journal of Power Electronics
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• 제11권5호
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• pp.713-718
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• 2011

This paper presents an online voltage disturbance estimator to achieve precise torque control of IPMSMs over a high speed operating region. The proposed design has a type of state-filter based on a Luenburger-style closed loop stator current vector observer. Utilizing the frequency response plot (FRF) approach, the estimation accuracy and the parameter sensitivities are analyzed. Accurate torque control and improved efficiency are provided with the decoupling of the effect of the parameter variations. The feasibility of the presented idea is verified by laboratory experiments.

• Journal of Advanced Marine Engineering and Technology
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• 제27권6호
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• pp.696-703
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• 2003

A photovoltaic power generation system is an infinite and clean energy system. Recently. because of the realization of high efficiency and low cost PV modules, the studies on the PV system have extensively increased. In this paper. we present an online scheme for parameter estimation of solar cell, based on the model adjustment technique and a real-coded genetic algorithm(RCGA). The ideal diode model and the diode model with series and shunt resistors are used to estimate their parameters, Simulation works using field data in the form of a V-I characteristic curve are carried out to demonstrate the effectiveness of the proposed method.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2007년도 하계학술대회 논문집
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• pp.391-393
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• 2007

The rotor speed and flux information is most important in the vector control. The accuracy of flux observers for induction machine inherently depends on parameter sensitivity. The control strategy is using online flux observer for flux estimation. In the proposed system, the speed control characteristics using a online flux observer control isn't affected by a load torque parameter disturbance. Simulation results are presented to prove the effectiveness of the adaptive sliding mode controller for the drive variable load of induction motor.

• Journal of international Conference on Electrical Machines and Systems
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• 제3권3호
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• pp.289-297
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• 2014

This paper proposed a novel high performance sensorless control scheme for IPMSM based on an extended nonlinear state observer. The gain-matrix of the observer has been derived by using state linearization method. Steady state errors in estimated rotor position and speed due to parameter inaccuracy have been analyzed, and an equivalent flux error is defined to represent the overall effect of parameter errors contributing to the wrong convergence of the estimated rotor speed as well as rotor position. Then, an online compensation strategy was proposed to limit the estimation errors in rotor position and speed. The effectiveness of the extended nonlinear state observer is validated through simulation and experimental test.

• 전력전자학회논문지
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• 제24권4호
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• pp.286-293
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• 2019

This study compares and analyzes online update techniques, which estimate the parameters of battery equivalent circuit models in real time. Online update techniques, which are based on extended Kalman filter and recursive least square methods, are constructed by considering the dynamic characteristics of batteries. The performance of the online update techniques is verified by simulation and experiments. Each online update technique is compared and analyzed in terms of complexity and accuracy to propose a suitable guide for selecting algorithms on various types of battery applications.

• Smart Structures and Systems
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• 제14권6호
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• pp.1247-1267
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• 2014

Real-Time Hybrid Simulation (RTHS) is a novel approach conceived to evaluate dynamic responses of structures with parts of a structure physically tested and the remainder parts numerically modelled. In RTHS, delay estimation is often a precondition of compensation; nonetheless, system delay may vary during testing. Consequently, it is sometimes necessary to measure delay online. Along these lines, this paper proposes an online delay estimation method using least-squares algorithm based on a simplified physical system model, i.e., a pure delay multiplied by a gain reflecting amplitude errors of physical system control. Advantages and disadvantages of different delay estimation methods based on this simplified model are firstly discussed. Subsequently, it introduces the least-squares algorithm in order to render the estimator based on Taylor series more practical yet effective. As a result, relevant parameter choice results to be quite easy. Finally in order to verify performance of the proposed method, numerical simulations and RTHS with a buckling-restrained brace specimen are carried out. Relevant results show that the proposed technique is endowed with good convergence speed and accuracy, even when measurement noises and amplitude errors of actuator control are present.

• Industrial Engineering and Management Systems
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• 제1권1호
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• pp.64-72
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• 2002

In the field of plant maintenance, data that are gathered by sensors on multiple machines are handled and analyzed. Online or pseudo online data handling is required on such fields. When the data occurrence speed exceeds the data handling speed, multiple data should be handled at a time (batch data handling or pseudo online data handling). If l amount of data are received at one time following N amount of data, how to estimate the new parameters effectively is a great concern. A new simplified calculation method, which calculates the N data's weights, is introduced. Numerical examples show that this new method has a fairly god estimation accuracy and the calculation time is less than 1/10 compared with the case when the whole data are re-calculated. Even under the restriction calculation ability in the apparatus is limited, this proposed method makes the failure detection of equipments possible in early stages with a few new coming data. This method would be applicable in many data handling fields.

• 제어로봇시스템학회논문지
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• 제14권8호
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• pp.779-784
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• 2008

This paper presents Kalman filter based system modeling algorithm for autonomous robot systems. State of the robot system is measured using embedded sensor systems and then carried to a host computer via ubiquitous sensor network (USN). We settle a linear state-space motion equation for unknown robot system dynamics and modify a popular Kalman filter algorithm in deriving suitable parameter estimation mechanism. To represent time-delay nature due to network media in system modeling, we construct an augmented state-space model which is mainly composed of original state and estimated parameter vectors. We conduct real-time experiment to test our proposed estimation algorithm where speed state of the constructed robot is used as system observation.