• The Journal of Korean Institute of Communications and Information Sciences
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• v.37C no.10
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• pp.1004-1010
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• 2012

In this paper, we propose the algorithm which considers applying recently proposed clock synchronization techniques with quite high accuracy in a few wireless sensor networks researches to time synchronization algorithm for multi-static radar system and especially overcomes the limitation of previous theory, cannot be applied between nodes in non-line of sight (NLOS). Proposed scheme estimates clock skew and clock offset using recursive robust least M-estimator with information of time stamp observations. And we improve the performance of algorithm by tracking and suppressing the time delays difference caused by NLOS system. Futhermore, this paper derive the mean square error (MSE) to present the performance of the proposed estimator and comparative analysis with previous methods.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.2
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• pp.133-140
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• 2016

In active sonar field, a target detection and localization based on a distributed sensor network has been much studied for the underwater surveillance of the coast. Zhou et al. proposed a target localization method utilizing the positions of target-detected sensors in distributed sensor network which consists of detection-only sensors. In contrast with a conventional method, Zhou's method dose not require to estimate the propagation model parameters of detection signal. Also it needs the lower computational complexity, and to transmit less data between network nodes. However, it has large target localization error. So it has been modified for reducing localization error by Ryu. Modified Zhou's method has better estimation performance than Zhou's method, but still relatively large estimation error. In this paper, a target localization method based on modified Zhou's method is proposed for reducing the localization error. The proposed method utilizes the geometry of the positions of target-detected sensors and a line that represents the bearing of target, a line can be found by modified Zhou's method. This paper shows that the proposed method has better target position estimation performance than Zhou's and modified Zhou's method by computer simulations.

• Journal of Korean Society of Transportation
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• v.14 no.3
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• pp.7-26
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• 1996

The estimation of real-time Origin-Destination(O-D) parameters, which gives travel demand between combinations of origin and destination points on a urban freeway network, from on-line surveillance traffic data is essential in developing an efficient ATMS strategy. On this need a real-time O-D parameter estimation model is formulated as a parameter adaptive filtering model based on the extended Kalman Filter. A Monte Carlo test have shown that the estimation of time-varying O-D parameter is possible using only traffic counts. Tests with field data produced the interesting finding that off-ramp volume predictions generated using a constant freeway O-D matrix was replaced by real-time estimates generated using the parameter adaptive filter.

• Journal of the Korea Institute of Military Science and Technology
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• v.7 no.4 s.19
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• pp.61-69
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• 2004

This paper presents a new analytical method for estimating the location of a target using directional data. Based on a nonlinear programming (NLP) problem formulated for the line method, which is a well known algorithm for two-dimensional location estimation, we present a method to find an optimal solution for the problem. Then we present a two-stage method for better location estimation based on the NLP problem. In addition, another two-stage method is presented for location estimation problems in which different types of observers are used to obtain directional data based on the analysis of the maximum likelihood estimate of the target location. The performance of the suggested method is evaluated through simulation experiments, and results show that the two-stage method is computationally efficient and highly accurate.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.1
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• pp.81-87
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• 2007

This paper proposes a new capacitance estimation scheme for a DC-link capacitor in a three-phase AC/DC/AC PWM converter. A controlled AC voltage with a lower frequency than the line frequency is injected into the DC-link voltage, which then causes AC power ripples at the DC side. By extracting the AC voltage and power components on the DC output side using digital filters, the capacitance can then be calculated using the Support Vector Regression (SVR). By training of SVR, a function which relates a given input (capacitor's power) and its corresponding output (capacitance value) can be derived. This function is used to predict outputs for given inputs that are not included in the training set. The proposed method does not require the information of DC-link current and can be simply implemented with only software and no additional hardware. Experimental results confirm that the estimation error is less than 0.16%.

• The Transactions of the Korean Institute of Power Electronics
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• v.8 no.2
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• pp.173-179
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• 2003

In this paper, a novel on-line dc capacitance estimation method for the three-phase PWM converter is proposed. At no load, input current at a low frequency is injected, which causes dc voltage ripple. With the at voltage and current ripple components of the dc side, the capacitance can be calculated. Experimental result shows that the estimation error is less than 2%.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.10a
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• pp.34-39
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• 1999

If the on-line cutting conditions (e.g. speed, feedrate, radial and axal depth of cuts) can be identified in an end milling process, much information about cutting forces will be estimated from the cutting force model. Therefore, those estimated conditions can be applied to monitoring and control areas. In this paper, a real-time estimation algorithm for radial and axial depth of cuts is studied in end milling using the averaging cutting forces per tooth. The analytical estimation models of depth of cuts are derived from the geometric cutting force model. The validity of the estimation models is verified on a horizontal machining center through the experiments in various cutting conditions.

• Journal of Power Electronics
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• v.16 no.6
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• pp.2150-2161
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• 2016

Mechanical and electrical parameter uncertainties cause dynamic and static estimation errors of the rotor speed and position, resulting in performance deterioration of sensorless control systems. This paper applies an extended nonlinear observer to interior permanent magnet synchronous motors (IPMSM) for the simultaneous estimation of the rotor speed and position. Two compensation methods are proposed to improve the observer performance against parameter uncertainties: an on-line rotational inertia adjustment approach that employs the gradient descent algorithm to suppress dynamic estimation errors, and an equivalent flux error compensation approach to eliminate static estimation errors caused by inaccurate electrical parameters. The effectiveness of the proposed control strategy is demonstrated by experimental tests.

• The Transactions of the Korean Institute of Power Electronics
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• v.15 no.4
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• pp.309-318
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• 2010

This paper presents a simulation model based on support vector regression (SVR) for flicker estimation emitted from the wind turbines. For the SVR training, the voltage variation and flicker level are selected as input and output, respectively. Through the off-line training, the relationship between the voltage variation and flicker level is derived. The required amount of data for the flicker measurement is decreased and its proessing time is also reduced. The simulation and experiment results have shown that the flicker estimation is performed accurately.

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.600-608
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• 2014

This paper presents estimation of d-axis and q-axis inductance of an interior permanent magnet synchronous motor (IPMSM) by using an extended Kalman filter (EKF). The EKF is widely used for control applications including the motor sensorless control and parameter estimation. The motor parameters can be changed by temperature and air-gap flux. In particular, the variation of the inductance affects torque characteristics like the maximum torque per ampere (MTPA) control. Therefore, by estimating the parameters, it is possible to improve the torque characteristics of the motor. The performance of the proposed estimator is verified by simulations and experimental results based on an 11kW PMSM drive system.