• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2003.03a
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• pp.481-490
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• 2003

This paper presents an efficient eigensolution method for non-proportionally damped systems. The proposed method is obtained by applying the accelerated Newton-Raphson technique and the orthonormal condition of the eigenvectors to the linearized form of the quadratic eigenproblem. A step length and a selective scheme are introduced to increase the convergence of the solution. The step length can be evaluated by minimizing the norm of the residual vector using the least square method. While the singularity may occur during factorizing process in other iteration methods such as the inverse iteration method and the subspace iteration method if the shift value is close to an exact eigenvalue, the proposed method guarantees the nonsingularity by introducing the orthonormal condition of the eigenvectors, which can be proved analytically. A numerical example is presented to demonstrate the effectiveness of the proposed method.

• Structural Engineering and Mechanics
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• v.5 no.2
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• pp.137-148
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• 1997

In computing eigenvalues for a large finite element system it has been observed that the eigenvalue extractors produce eigenvectors that are in some sense more accurate than their corresponding eigenvalues. From this observation the paper uses a patch type technique based on the eigenvector for one mesh quality to provide an eigenvalue error indicator. Tests show this indicator to be both accurate and reliable. This technique was first observed by Stephen and Steven for an error estimation for buckling and natural frequency of beams and two dimensional in-plane and out-of-plane structures. This paper produces and error indicator for the more difficult problem of three dimensional brick elements.

• Journal of applied mathematics & informatics
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• v.25 no.1_2
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• pp.435-443
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• 2007

Computing the interior spectrum of large sparse generalized eigenvalue problems $Ax\;=\;{\lambda}Bx$, where A and b are large sparse and SPD(Symmetric Positive Definite), is often required in areas such as structural mechanics and quantum chemistry, to name a few. Recently, CG-type methods have been found useful and hence, very amenable to parallel computation for very large problems. Also, as in the case of linear systems proper choice of preconditioning is known to accelerate the rate of convergence. After the smallest eigenpair is found we use the orthogonal deflation technique to find the next m-1 eigenvalues, which is also suitable for parallelization. This offers advantages over Jacobi-Davidson methods with partial shifts, which requires re-computation of preconditioner matrx with new shifts. We consider as preconditioners Incomplete LU(ILU)(0) in two variants, ever-relaxation(SOR), and Point-symmetric SOR(SSOR). We set m to be 5. We conducted our experiments on matrices from discretizations of partial differential equations by finite difference method. The generated matrices has dimensions up to 4 million and total number of processors are 32. MPI(Message Passing Interface) library was used for interprocessor communications. Our results show that in general the Multi-Color ILU(0) gives the best performance.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.13 no.10
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• pp.989-997
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• 2002

This paper presents a new technique that enhances the performance of the smart antenna system especially in signal environments of wide angular spread by adopting a weight vector obtained from two eigenvectors of theautocovariance matrix of the received data. While the conventional beamformingtechnique employs only one eigenvector corresponding to the largest eigenvalue, the proposed algorithm uses two eigenvectors corresponding to the largest and second largest eigenvalue in such a way that it can be robust enough to the signal environments of wide angular spread. An efficient adaptive procedure is shown to verify that the optimal weight vector consisting of the two eigenvectors is obtained with a reasonable complexity(3.5$N_2$+ 12N) and accuracy. it is also shown in this paper that the numerical results obtained from the proposed adaptive procedure well agree with those obtained from a commercial tool computing the eigen-function of MATLABTM.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.3 no.1
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• pp.99-106
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• 1999

An accelerated optimization technique combined with a stepwise deflation procedure is presented for the efficient evaluation of a few of the smallest eigenvalues and their corresponding eigenvectors of the generalized eigenproblems. The optimization is performed on the Rayleigh quotient of the deflated matrices by the aid of a preconditioned conjugate gradient scheme with the incomplete Cholesky factorization.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.96-100
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• 1990

Dynamic modelling and controller design technique for constant-frequency series resonant converter with buck type preregulator are mainly described in this paper. An equivalent circuit model is derived and a state equation is developed from this model. To improve the dynamic performance, a negative feedback of inductor current is added to the proportional and integral control of output voltage. Furthermore, an optimization technique with prescribed eigenvalue region is applied to the determination of feedback gains. With the presented design method, much better dynamic performance can be obtained.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.52 no.5
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• pp.271-278
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• 2003

Power system stability is correlated with system structure, disturbances and operating conditions, and power flows on transmission lines are closely related with those conditions. This paper proposes a methodology to identify correlative power flows for power system transient and small-signal stability prediction. In transient stability sense, the Critical Clearing Time is used to select some dominant contingencies, and Transient Stability Prediction index is proposed for the quantitative comparison. For small-signal stability, this paper discusses a methodology to identify crucial transmission lines for stability Prediction by introducing a sensitivity factor based on eigenvalue sensitivity technique. On-line monitoring of the selected lines enables to predict system stability in real-time. Also, a Procedure to make a priority list of monitored transmission lines is proposed. The procedure is applied to a test system and the KEPCO systems in the year of 2003 and it shows capabilities of the proposed method

• Journal of Electrical Engineering and Technology
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• v.2 no.4
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• pp.428-433
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• 2007

This paper describes the new eigenvalue algorithm exploiting the Implicit Restarted Arnoldi Method (IRAM) and its application to power systems. IRAM is a technique for combining the implicitly shifted mechanism with a k-step Arnoldi factorization to obtain a truncated form of the implicitly shifted QR iteration. The numerical difficulties and storage problems normally associated with the Arnoldi process are avoided. Two power systems, one of which has 36 state variables and the other 150 state variables, have been tested using the ARPACK program, which uses IRAM, and the eigenvalue results are compared with the results obtained from the conventional QR method.

• Proceedings of the KIEE Conference
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• 1995.11a
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• pp.83-85
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• 1995

A technique for power system' stabilization is presented using the variable structure control theory. The selection problem of the proper switching vector is very important subject for a design of the variable structure controller. In this paper, the switching vector is selected by desired eigenvalues allocation. and these desired eigenvalues are determined by eigenvalue assignment. Simulation results show that eigenvalue allocation variable structure stabilizer yields better dynamic performance than the others (conventional PSS, optimal linear stabilizer) and is robust to wide variations of the system parameters.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.10-10
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• 2000

Eigenstructure assignment is a typical method with the capability of the consideration of the specifications in time-domain in designing a 1]near control system. In general eigenstructure assignment such that all the desired eigenvalues are exactly assigned to the closed-loop system, the assignment of the eigenvectors is very restrictive. However if the arbitrary point in a certain area as an eigenvalue is allowed to be assigned t the closed-loop system, the assignment of the eigenvector corresponding to this eigenvalue can be much less restrictive. In this paper, the flexible eigenstructure assignment that can assign more closely the desired eigenvector to the closed-loop system by using an optimization technique is proposed.