• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.26 no.12
• /
• pp.2631-2635
• /
• 2002

The semi-analytic sensitivity analysis using Pade approximation is presented for linear elastic structures. Although the semi-analytic method has several advantages, accuracy of the method prevents it from practical application. One of promising remedies is the use of geometric series for the matrix inversion. Though series expansion of order three has been successfully applied to the calculation of the structural sensitivity in the most range of the design perturbation, it is prone to have a slow convergence for large perturbation. To overcome this shortage, Pade approximation is introduced so that it can broaden the trust region of the perturbation without adding expansion terms. Numerical results show that the confident sensitivity can be obtained with tiny expenses of computation effort.

• Structural Monitoring and Maintenance
• /
• v.4 no.1
• /
• pp.53-68
• /
• 2017

The response sensitivity method in time domain has been applied extensively for damage identification. In this paper, the relationship between the error of damage identification and the sensitivity matrix is investigated through perturbation analysis. An index is defined according to the perturbation amplify effect and an optimal sensor placement method is proposed based on the minimization of that index. A sequential sub-optimal algorithm is presented which results in consistently good location selection. Numerical simulations with a two-dimensional high truss structure are conducted to validate the proposed method. Results reveal that the damage identification using the optimal sensor placement determined by the proposed method can identify multiple damages of the structure more accurately.

• Journal of Institute of Control, Robotics and Systems
• /
• v.3 no.1
• /
• pp.17-22
• /
• 1997

The stability robustness problem of linear discrete-time systems with time-varying perturbations is considered. By using Lyapunov direct method, the perturbation bounds for guaranteeing the quadratic stability of the uncertain systems are derived. In the previous results, the perturbation bounds are derived by the quadratic equation stemmed from Lyapunov method. In this paper, the bounds are obtained by a numerical optimization technique. Linear matrix inequalities are proposed to compute the perturbation bounds. It is demonstrated that the suggested bound is less conservative for the uncertain systems with unstructured perturbations and seems to be maximal in many examples. Furthermore, the suggested bound is shown to be maximal for the special classes of structured perturbations.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.30 no.7
• /
• pp.98-104
• /
• 2002

System condensation technique improves the efficiency of the inverse perturbation method of damage detection developed in the previous work. The technique is applied to transform the unmeasured DOFs to the measured DOFs. This approach makes it possible to eliminate the unmeasured DOFs, which accelerates the computational efficiency. The numerical instability problems due to the system condensation technique are also resolved by updating the transformation matrix for each step, and also by adopting the accelerated improved reduced system(AIRS) condensation method.

• Kyungpook Mathematical Journal
• /
• v.62 no.1
• /
• pp.107-118
• /
• 2022

In this note we observe that any truncated multi-index sequence has an interpolating measure supported in Euclidean space. It is well known that the consistency of a truncated moment sequence is equivalent to the existence of an interpolating measure for the sequence. When the moment matrix of a moment sequence is nonsingular, the sequence is naturally consistent; a proper perturbation to a given moment matrix enables us to confirm the existence of an interpolating measure for the moment sequence. We also illustrate how to find an explicit form of an interpolating measure for some cases.

• Journal of Institute of Control, Robotics and Systems
• /
• v.14 no.12
• /
• pp.1270-1277
• /
• 2008

A Haar wavelet based numerical method for solving singularly perturbed linear time invariant system is presented in this paper. The reduced pure slow and pure fast subsystems are obtained by decoupling the singularly perturbed system and differential matrix equations are converted into algebraic Sylvester matrix equations via Haar wavelet technique. The operational matrix of integration and its inverse matrix are utilized to reduce the computational time to the solution of algebraic matrix equations. Finally a numerical example is given to demonstrate the validity and applicability of the proposed method.

• Journal of the Korean Data and Information Science Society
• /
• v.18 no.1
• /
• pp.229-235
• /
• 2007

Measures of leverage in nonlinear regression models are discussed by extending the leverage in linear regression models. The connection between measures of leverage and nonlinearity of the models are explored. Illustrative example based on real data is presented.

• Proceedings of the Korean Society for Bioinformatics Conference
• /
• 2004.11a
• /
• pp.265-271
• /
• 2004

The interaction network of protein -protein plays an important role to understand the various biological functions of cells. Currently, the high -throughput experimental techniques (two -dimensional gel electrophoresis, mass spectroscopy, yeast two -hybrid assay) provide us with the vast amount of data for protein-protein interaction at the proteome scale. In order to recognize the role of each protein in their network, the efficient bioinformatical and computational analysis methods are required. We propose a systematic and mathematical method which can analyze the protein -protein interaction network rigorously and enable us to capture the biological and physical essence of a topological character and stability of protein -protein network, and sensitivity of each protein along the biological pathway of their network. We set up a Laplacian matrix of spectral graph theory based on the protein-protein network of yeast proteome, and perform an eigenvalue analysis and apply a perturbation method on a Laplacian matrix, which result in recognizing the center of protein cluster, the identity of hub proteins around it and their relative sensitivities. Identifying the topology of protein -protein network via a Laplacian matrix, we can recognize the important relation between the biological pathway of yeast proteome and the formalism of master equation. The results of our systematic and mathematical analysis agree well with the experimental findings of yeast proteome. The biological function and meaning of each protein cluster can be explained easily. Our rigorous analysis method is robust for understanding various kinds of networks whether they are biological, social, economical...etc

• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.54 no.1
• /
• pp.17-25
• /
• 2005

This paper provides sufficient conditions for the robustness of Affine linear TFM(Transfer Function Matrix) MIMO (Multi-Input Multi-Output) uncertain systems based on Rosenbrock's DNA (Direct Nyquist Array). The parametric uncertainty is modeled through a Affine TFM MIMO description, and the unstructured uncertainty through a bounded perturbation of Affine polynomials. Gershgorin's theorem and concepts of diagonal dominance and GB(Gershgorin Bands) are extended to include model uncertainty. For this type of parametric robust performance we show robustness of the Affine TFM systems using Nyquist diagram and GB, DNA(Direct Nyquist Array). Multiloop PI/PB controllers can be tuned by using a modified version of the Ziegler-Nickels (ZN) relations. Simulation examples show the performance and efficiency of the proposed multiloop design method.

• Journal of the Korean Mathematical Society
• /
• v.54 no.2
• /
• pp.613-626
• /
• 2017

For the overdetermined linear system, when both the data matrix and the observed data are contaminated by noise, Total Least Squares method is an appropriate approach. Since an ill-conditioned data matrix with noise causes a large perturbation in the solution, some kind of regularization technique is required to filter out such noise. In this paper, we consider a Dual regularized Total Least Squares problem. Unlike the Tikhonov regularization which constrains the size of the solution, a Dual regularized Total Least Squares problem considers two constraints; one constrains the size of the error in the data matrix, the other constrains the size of the error in the observed data. Our method derives two nonlinear equations to construct the iterative method. However, since the Jacobian matrix of two nonlinear equations is not guaranteed to be nonsingular, we adopt a trust-region based iteration method to obtain the solution.