• 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.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.4
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• pp.393-400
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• 2011

In this study, a procedure for the inverse estimation of the fatigue life parameters of springs which utilize the field fatigue life test data is proposed to replace real test with the FEA on fatigue life prediction. The Bayesian approach is employed, in which the posterior distributions of the parameters are determined conditional on the accumulated life data that are routinely obtained from the regular tests. In order to obtain the accurate samples from the distributions, the Markov chain Monte Carlo (MCMC) technique is employed. The distributions of the parameters are used in the FEA for predicting the fatigue life in the form of a predictive interval. The results show that the actual fatigue life data are found well within the posterior predictive distributions.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.5C
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• pp.384-392
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• 2012

Recently, much research on blind estimation of the interleaver parameters has been performed by using Gauss-Jordan elimination to find the linearity of the block channel code. When using Gauss-Jordan elimination, the input data to be calculated needs to run as long as the square multiple of the number of the interleaver period. Thus, it has a limit in estimating the interleaver parameters with insufficient input data. In this paper, we introduce and analyze an estimation algorithm which can estimate interleaver parameters by using only 15 percent of the input data length required in the above algorithm. The shorter length of input data to be calculated makes it possible to estimate the interleaver parameters even when limited data is received. In addition, a 80 percent reduction in the number of the interleaver period candidates increases the efficiency of analysis. It is also feasible to estimate both the type and size of the interleaver and the type of channel coding.

• Explosives and Blasting
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• v.41 no.3
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• pp.73-92
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• 2023

With the increase of risk of gas explosion, various methods for indirectly estimating the explosion paramaters, which are required for the prediction of gas explosion scale and impact. In this study, the characteristics of the most frequently used methods such as TNT equivalent method, TNO multi-energy method, and BST method and the processes for determining the parameters of the methods were compared. In the case of TNT equivalent method, an adequate selection of the efficiency factor for various conditions such as the type of vapor cloud explosion and explosion material is needed. There is no objective guidelines for the selection of class number in TNO multi-energy method and it is not possible to estimate negative overpressure. It was found that there were some mistakes in the reported parameter values and suggested corrected values. BST method provides more detailed guidelines for the estimation of the explosion parameters including negative overpressure, but the graphs used in this methods are not clear. In order to overcome the problem, the graphs were redrawn. A more convenient estimation of explosion parameters with the numerical expression of the redrawn graphs will be available in the future.

• International Journal of Control, Automation, and Systems
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• v.6 no.3
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• pp.320-326
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• 2008

This paper studies the problem of fault estimation using adaptive fault diagnosis observer. A fast adaptive fault estimation (FAFE) approximator is proposed to improve the rapidity of fault estimation. Then based on linear matrix inequality (LMI) technique, a feasible algorithm is explored to solve the designed parameters. Furthermore, an extension to sensor fault case is investigated. Finally, simulation results are presented to illustrate the efficiency of the proposed FAFE methodology.

• Journal of Korean Society for Quality Management
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• v.9 no.1
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• pp.51-60
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• 1981

This paper deals with the estimation of the Weibull parameters, which have a close relation with product reliability characteristics. Among the many kinds of estimation methods, Ishikawa's Weibull Probability Paper (WPP) is commonly used. The WPP is very convenient, but it has a great disadvantage in estimation accuracy by plotting method. It is very difficult to get the same results even if one use the same data several times. A computer program for the regression method is used for the parameter estimation to reduce these errors.

• Journal of Information Technology Applications and Management
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• v.14 no.4
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• pp.1-16
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• 2007

In the microcell- or picocell-based system the frequent movements of the mobile bring about excessive traffics into the networks. A mobile location estimation mechanism can facilitate both efficient resource allocation and better QoS provisioning through handoff optimization. Existing location estimation schemes consider only LOS model and have poor performance in presence of multi-path and shadowing. In this paper we study a novel scheme which can increase estimation accuracy by considering NLOS environment and other multiple decision parameters than the received signal strength.

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.1
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• pp.62-74
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• 2002

The tracking of a reference temperature trajectory in a polymerization batch reactor is a common problem and has critical importance because the quality control of a batch reactor is usually achieved by implementing the trajectory precisely. In this study, only energy balances around a reactor are considered as a design model for control synthesis, and material balances describing concentration variations of involved components are treated as unknown disturbances, of which the effects appear as time-varying parameters in the design model. For the synthesis of a tracking controller, a method combining the input-output linearization of a time-variant system with the parameter estimation is proposed. The parameter estimation method provides parameter estimates such that the estimated outputs asymptotically follow the measured outputs in a specified way. Since other unknown external disturbances or uncertainties can be lumped into existing parameters or considered as another separate parameters, the method is useful in practices exposed to diverse uncertainties and disturbances, and the designed controller becomes robust. And the design procedure and setting of tuning parameters are simple and clear due to the resulted linear design equations. The performances and the effectiveness of the proposed method are demonstrated via simulation studies.

• Wind and Structures
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• v.26 no.6
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• pp.383-395
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• 2018

An accurate determination of wind speed distribution is the basis for an evaluation of the wind energy potential required to design a wind turbine, so it is important to estimate unknown parameters of wind speed distribution. In this paper, Gumbel distribution is used in modelling wind speed data, and alternative robust estimation methods to estimate its parameters are considered. The methodologies used to obtain the estimators of the parameters are least absolute deviation, weighted least absolute deviation, median/MAD and least median of squares. The performances of the estimators are compared with traditional estimation methods (i.e., maximum likelihood and least squares) according to bias, mean square deviation and total mean square deviation criteria using a Monte-Carlo simulation study for the data with and without outliers. The simulation results show that least median of squares and median/MAD estimators are more efficient than others for data with outliers in many cases. However, median/MAD estimator is not consistent for location parameter of Gumbel distribution in all cases. In real data application, it is firstly demonstrated that Gumbel distribution fits the daily mean wind speed data well and is also better one to model the data than Weibull distribution with respect to the root mean square error and coefficient of determination criteria. Next, the wind data modified by outliers is analysed to show the performance of the proposed estimators by using numerical and graphical methods.

• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.1
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• pp.1-10
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• 2020

Effective jamming in electronic warfare depends on proper jamming technique selection and jamming parameter estimation. For this purpose, this paper proposes a new method of estimating jamming parameters using Gaussian kernel function networks. In the proposed approach, a new method of determining the optimal structure and parameters of Gaussian kernel function networks is proposed. As a result, the proposed approach estimates the jamming parameters in a reliable manner and outperforms other methods such as the DNN(Deep Neural Network) and SVM(Support Vector Machine) estimation models.