• The Transactions of the Korean Institute of Power Electronics
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• v.23 no.1
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• pp.66-71
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• 2018

We propose an online parameter estimation method for surface-mounted permanent-magnet synchronous motor (SPMSM) using an affine projection algorithm (APA). The proposed method estimates parameters with two APAs based on the discrete-time model equation of SPMSM during motor operation. The first APA is designed to estimate inductance, and the second APA is designed to estimate resistance and flux linkage. However, in case when the d-axis current is controlled to 0A, the second APA cannot estimate resistance and flux linkage simultaneously because the matrix rank in APA becomes deficient. To overcome this problem, we temporarily inject a negative reference current input to the d-axis control loop, and the matrix in the APA then becomes full rank, which enables the simultaneous estimation of resistance and flux linkage. The proposed method is verified by PSIM simulation and an actual experiment, and the results reveal that SPMSM parameters can be estimated online during motor operation.

• Proceedings of the Korean Statistical Society Conference
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• 2005.05a
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• pp.135-140
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• 2005

• Journal of Korea Water Resources Association
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• v.42 no.4
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• pp.331-341
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• 2009

In this study, we compared the observed information matrix with the Fisher information matrix to estimate the uncertainty of maximum likelihood estimators of the generalized logistic (GL) distribution. The previous literatures recommended the use of the observed information matrix because this is convenient since this matrix is determined as the part of the parameter estimation procedure and there is little difference in accuracy between the observed information matrix and the Fisher information matrix for large sample size. The observed information matrix has been applied for the generalized logistic distribution based on the previous study without verification. For this purpose, a simulation experiment was performed to verify which matrix gave the better accuracy for the GL model. The simulation results showed that the variance-covariance of the ML parameters for the GL distribution came up with similar results to those of previous literature, but it is preferable to use of the Fisher information matrix to estimate the uncertainty of quantile of ML estimators.

• Honam Mathematical Journal
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• v.33 no.4
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• pp.487-493
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• 2011

The Fisher information matrix plays a significant role in statistical inference in connection with estimation and properties of variance of estimators. In this paper, we define the parameter space of the t-manifold using its Fisher's matrix and characterize the t-manifold from the viewpoint of information geometry. The ${\alpha}$-scalar curvatures to the t-manifold are calculated.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.04a
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• pp.191-196
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• 2004

This study proposed the analysis of mass position detection and modified stiffness due to the change of the mass and stiffness of structure by using the original and modified dynamic characteristics. The method is applied to examples of a cantilever and 3 degree of freedom by modifying the mass. The predicted detection of mass positions and magnitudes are in good agrement with these from the structural reanalysis using the modified mass.

• Journal of Power System Engineering
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• v.3 no.4
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• pp.69-78
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• 1999

In the single-input and single-output system, the parameter of plant is scalar polynomial, but in the multiple input and multiple output, it accompanies, being matrix polynomial, the consideration of observable controlability index or problems non-commutation in matrix polynomial as well as degree, and it is more complex to deal with. Therefore, it is thought that a full research on the single-input and single-output system is not sufficient. This paper proposes that problems of minimum variance self-tuning regulator by using numerical calculation example of multivariable system and pole assignment self-tuning regulator.

• IEMEK Journal of Embedded Systems and Applications
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• v.4 no.2
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• pp.97-102
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• 2009

In this paper, the problem of stability analysis for networked control systems with norm-bounded parameter uncertainties is investigated. By construction Lyapunov's functional, a new delay-dependent stability criterion for uncertain networked control system is established in terms of LMIs (linear matrix inequalities) which can be easily by various convex optimization algorithms. One numerical example is included to show the effectiveness of proposed criterion.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.36 no.4
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• pp.287-292
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• 1987

This paper deals with applications of Haar functions to parameter identification of linear systems. It is first introuduced to a new operational matrix which relates Haar functions and their integrations. The matrix can be used to identify the parameters of unknown linear systems by a least squares estimation. And then, the state equation of given systems is transformed into a computationally convenient algebraic form. This approach provides a more efficient method for the system identification problem.

• The Pure and Applied Mathematics
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• v.2 no.2
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• pp.133-140
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• 1995

The D-optimal design criterion for precise parameter estimation in nonlinear regression analysis is called the determinant criterion because the determinant of a matrix is to be maximized. In this thesis, we derive the gradient and the Hessian of the determinant criterion, and apply a QR decomposition for their efficient computations. We also propose an approximate form of the Hessian matrix which can be calculated from the first derivative of a model function with respect to the design variables. These equations can be used in a Gauss-Newton type iteration procedure.

• Journal of Applied Reliability
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• v.3 no.2
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• pp.127-136
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• 2003

This paper investigates the effect of individual observations in regression models with MA(1) errors through the 'hat matrix' It shows that the first observation has the largest hat matrix diagonal component for $\theta$＜0 in the regression model with an intercept. This provides additional evidence for retaining the first observation in performing estimation in this setting. When the regression model goes to the origin and the independent variable has a deterministic trend, the last observation has the greatest leverage for │$\theta$│＜1 and may have potentially large impact on parameter estimation.