• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.10
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• pp.1264-1271
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• 1999

In this paper, an efficient method of analysis and design of fault detection filter is presented. Since the directional constraint is applied to the eigenstructure associated with the detection space, an eigenvector is determined by the eigenvalues associated with other eigenvectors. Further, the assignment of a pair of eigenvalue and eigenvector leads to the fixation of overall eigenstructure related with the detection space. Using the transmission zeros and the transmission zero vectors, these phenomenon are clearly proven, and an efficient algorithm for design of the fault detection filters is presented.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.68.3-68
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• 2001

We describe the looper controller design for a hot strip mill. The looper is to control the strip tension which influences on the width of the strip. It is very important to control the looper control of the hot strip mill, but difficult to control the looper, because there exists mutual interaction among strip gauge, looper angle, and strip tension. In this paper, we present the modeling for the looper of a hot strip mill to control the tension of the strip and suggest a eigenstructure assignment method. The eigenstructure assignment is useful tool that allows the designer to satisfy damping, settling time, and mode decoupling specifications directly by choosing eigenvalue and eigenvectors. Desired eigenvalue and eigenvector are chosen to satisfy the desired responses.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.04a
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• pp.39-44
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• 2003

It was shown that the robustness of deterministic observers with respect to modeling errors, measurement bias and round-off errors can be represented by a single performance index the condition number of the observer eigenvector matrix. In this paper, a robust observer for multi-output systems is designed using the left eigenstructure assignment, where the observer gain can not be determined uniquely with respect to the desired observer poles. Utilizing the eigenstructuer assignment for the robustness of the observer, the desired eigenvector matrix is selected to achieve the observer eigenvector matrix with the small condition number. The performance of the designed robust observer is evaluated in a spindle-drive simulation example where the load speed to be estimated based on the measured signals.

• Proceedings of the KSME Conference
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• 2000.04a
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• pp.499-504
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• 2000

Since large space structures(LSS) such as a space station, a solar power station satellite, etc., are theoretically distributed parameter and infinite-dimensional system, they have to be modeled into large finite-dimensional systems for control system design. Besides, there are fundamental problems in active vibration control of the large flexible structures. For example, a modeled large finite-dimensional system must be controlled with a much smaller dimensional controller. This causes the spillover phenomenon which degrades the control performances and reduces the stability margin. Furthermore, it may destabilize the entire feedback control system. In this paper, we proposed a novel control method for spillover suppression in the control of large flexible structures by using eigenstructure assignment. Its effectiveness in spillover suppression is investigated and verified by the numerical experiments using an example of the simply supported flexible beam which is modeled to have four controlled modes and eight uncontrolled modes.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.2
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• pp.206-213
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• 2001

An overlapping decentralized robust EA(eigenstructure assignment) controller is designed for an active suspension system of a vehicle based on a full car model with 7-degree of freedom. Using overlapping decomposition, the full car model is decentralized by two half car models. For each half car model, an effective and disturbance suppressible controller can be obtained by assigning appropriately a left eigenstructure of the system. The performance of the proposed overlapping decentralized robust EA controller is compared with that of a conventional centralized EA controller through computer simulations.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.3
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• pp.226-231
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• 2008

In this paper, we propose novel eigenstructure assignment method in full-state feedback for linear time-invariant MIMO system such that directions of some left eigenvectors are exactly assigned to the desired directions. It is required to consider the direction of left eigenvector in designing eigenstructure of closed-loop system, because the direction of left eigenvector has influence over excitation by associated input variables in time-domain response. Exact direction of a left eigenvector can be achieved by assigning proper right eigenvector set satisfying the conditions of the presented theorem based on Moore's theorem and the orthogonality of left and right eigenvector. The right eigenvector should reside in the subspace given by the desired eigenvalue, which restrict a number of designable left eigenvector. For the two cases in which desired eigenvalues are all real and contain complex number, design freedom of designable left eigenvector are given.

• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.12
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• pp.1522-1531
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• 1988

The purpose of this paper is to explain eigenstructure based spatial spectrum estimation algorithms computing better estimates than the other approaches. Also, as an approach to overcome performance degradations in a multipath environments, the notion of forward and backwark spatial smoothing is discussed. Intensive simulation results,which include the comparisons of the eigenbased spatial spectral estimation algorithms in the situations of faulty estimation of the number of signals, are presented. The simulation results have shown that overestimation of the number of signals is more desirable than underestimation in using EV (Eigen Vector) and MUSIC (Multiple Signal Classification) algorithms and that underestimation of the number of signals is better strategy than overestimation in using eigenstructure based LP(Linear Prediction) algorithms.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.11
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• pp.81-88
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• 1999

A conventional quarter-car suspension system is a single input system with one actuator. Thus, the performance enhancement for ride quality could be limited. In this paper, we propose a novel automotive suspension system for a quarter-car with two independent actuators to improve the control performance. The left eigenstructure assignment method for multi-variable systems has been applied to the proposed novel quarter-car model.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.11
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• pp.1621-1628
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• 2004

This paper proposes a design methodology for the robust observer using the eigenstructure assignment in multi-output systems so that the observer is less sensitive to the ill-conditioning factors such as unknown initial estimation error, modeling error and measurement bias in transient and steady-state observer performance. The robustness of the observer can be achieved by selecting the desired eigenvector matrix to have a small condition number that guarantees the small upper bound of the estimation error. So the left singular vectors of the unitary matrix spanned by space of the achievable eigenvectors are selected as a desired eigenvectors. Also, this paper proposes how to select the desired eigenvector based on the measure of observability and designs the observer with small gain. An example of a spindle drive system is simulated to validate the robustness to the ill-conditioning factors in the observer performance.

• Communications for Statistical Applications and Methods
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• v.12 no.3
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• pp.653-657
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• 2005

Eigenstructure of a spatial design matrix of Matheron's variogram estimator in $R^1$ is derived. It is shown that the spatial design matrix in $R^1$ with n/2$\le$h < n has a nice spectral decomposition. The mean, variance, and covariance of this estimator are obtained using the eigenvalues of a spatial design matrix. We also found that the lower bound and the upper bound of the normalized Matheron's variogram estimator.