• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.109-112
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• 1997

In this note, we investigate a noniterative design method of an observer-based robust H$\_$2/ controller in the presence of structured real parameter uncertainty by applying Riccati approach based on the guaranteed cost function. Motivated by the numerical difficulty of the problem, we try to develop a simple design method named as block-diagonal approach, which can be solved by the LMIs method. By assuming the block-diagonal structure of Riccati solution, the original problem can be derived into two sequentially decoupled optimization problems as LQG control problem. The proposed method seems to be numerically efficient in obtaining a feasible compensator.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.988-991
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• 1996

The purpose of this thesis is to develop methods of designing robust LQR/LQG controllers for time-varying systems with real parametric uncertainties. Controller design that meet desired performance and robust specifications is one of the most important unsolved problems in control engineering. We propose a new framework to solve these problems using Linear Matrix Inequalities (LMls) which have gained much attention in recent years, for their computational tractability and usefulness in control engineering. In Robust LQR case, the formulation of LMI based problem is straightforward and we can say that the obtained solution is the global optimum because the transformed problem is convex. In Robust LQG case, the formulation is difficult because the objective function and constraint are all nonlinear, therefore these are not treatable directly by LMI. We propose a sequential solving method which consist of a block-diagonal approach and a full-block approach. Block-diagonal approach gives a conservative solution and it is used as a initial guess for a full-block approach. In full-block approach two LMIs are solved sequentially in iterative manner. Because this algorithm must be solved iteratively, the obtained solution may not be globally optimal.

• Korean Management Science Review
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• v.24 no.1
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• pp.91-111
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• 2007

In this paper an effective two-phase approach adopting modified p-median mathematical model is proposed for grouping machines and parts in cellular manufacturing(CM). Unlike the conventional methods allowing machines and parts to be improperly assigned to cells and families, the proposed approach seeks to find the proper block diagonal solution where all the machines and parts are properly assigned to their most associated cells and families in term of the actual machine processing and part moves. Phase 1 uses the modified p-median formulation adopting new inter-machine similarity coefficient based on the non-binary production data-based part-machine incidence matrix(PMIM) that reflects both the operation sequences and production volumes for the parts to find machine cells. Phase 2 apollos iterative reassignment procedure to minimize inter-cell part moves and maximize within-cell machine utilization by reassigning improperly assigned machines and parts to their most associated cells and families. Computational experience with the data sets available on literature shows the proposed approach yields good-quality proper block diagonal solution.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2001.10a
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• pp.21-24
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• 2001

This study is concerned with the development of efficient p-median approach to nondegenerate cell formation(CF) in group technology(GT) manufacturing. Unlike most of existing CF methodologies allowing degenerate cells or families that contains no parts or machines, this study attempts to find cell configuration where each machine cell contains at least two or more machines processing at least two or more parts so as to fully utilize the similarity in designing and processing parts. Nondegenerate CF seeks to minimize both the exceptional elements outside the diagonal block and the voids within the diagonal block. To find nondegenerate cells, a two-phase p-median methodology is proposed. In phase 1, the classical p-median model is implemented to find initial cells. In phase 2, bottleneck machines and parts are reassigned until no further degenerate cells and families are found. Test results on moderately medium-sized CF problems show the substantial efficiency of the proposed approach.

• Journal of the Korean Operations Research and Management Science Society
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• v.31 no.4
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• pp.69-87
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• 2006

This paper proposes an effective approach for the part-machine grouping(PMG) based on the non-binary part-machine incidence matrix in which real manufacturing factors such as the operation sequences with multiple visits to the same machine and production volumes of parts are incorporated and each entry represents actual moves due to different operation sequences. The proposed approach adopts Fuzzy ART neural network to quickly create the Initial part families and their machine cells. A new performance measure to evaluate and compare the goodness of non-binary block diagonal solution is suggested. To enhance the poor solution due to category proliferation inherent to most artificial neural networks, a supplementary procedure reassigning parts and machines is added. To show effectiveness of the proposed approach to large-size PMG problems, a psuedo-replicated clustering procedure is designed. Experimental results with intermediate to large-size data sets show effectiveness of the proposed approach.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.10
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• pp.1311-1316
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• 1999

A visual servoing method has been proposed based on disturbance observer to eliminate the effect of the off-diagonal component of image feature Jacobian, since performance indices such as measurement sensitivity of visual features, sensitivity of the control to noise and controllability could be improved when an image feature Jacobian was given as a block diagonal matrix. In this paper, experimental results of disturbance observer-based visual servoing are discussed where Samsung FARAMAN-AS1 6-axis industrial robot manipulator is employed. Also, the feature saturator is proposed to stabilize the disturbance observer loop by saturating the differential changes of the image features.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.3077-3079
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• 1999

A visual servoing method has been proposed based on disturbance observer to eliminate the effect of the off-diagonal component of image feature Jacobian, since performance indices such as measurement sensitivity of visual features, sensitivity of the control to noise and controllability could be improved when an image feature Jacobian was given as a block diagonal matrix. In this paper, experimental results of disturbance observer-based visual servoing are discussed where Samsung FARAMAN-ASl 6-axis industrial robot manipulator is employed. Also, the feature saturator is proposed to stabilized the disturbance observer loop by saturating the differential changes of the image features.

• The Bulletin of The Korean Astronomical Society
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• v.37 no.2
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• pp.160.1-160.1
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• 2012

We present an alternative approach for satellite formation reconfiguration by an optimal impulsive-thrust strategy to minimize the total characteristic velocity in a near-circular-orbit. Linear transformation decouples the Hill-Clohessy-Wiltshire(HCW) dynamics into a new block-diagonal system matrix consisting of 1-dimensional harmonic oscillator and 2-dimensional subsystem. In contrast to a solution based on the conventional primer vector theory, the optimal solution and the necessary conditions are represented as times and directions of impulses. New analytical expression of the total characteristic velocity is found for each sub systems under general boundary conditions including transfer time constraint. To minimize the total characteristic velocity, necessary conditions for times and directions of impulses are analytically solved. While the solution to the 1-dimensional harmonic oscillator has been found, the solution to the 2-dimensional subsystem is currently under construction. Our approach is expected to be applicable to more challenging problems.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.11a
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• pp.656-658
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• 2006

This study deals with the part-machine grouping (PMG) that considers realistic manufacturing factors, such as the machine duplication, operation sequences with multiple visits to the same machine, and production volumes of parts. Basically, this study is an extension of Won(2006) that has adopted fuzzy ART neural network to group parts and machines. The proposed fuzzy ART neural network algorithm is implemented with an ancillary procedure to enhance the block diagonal solution by rearranging the order of input presentation. Computational experiments applied to large-size PMG data sets with a psuedo-replicated clustering procedure show effectiveness of the proposed approach.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.348-351
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• 1995

This note proposes a robust LQR method for systems with structured real parameter uncertainty based on Riccati equation approach. Emphasis is on the reduction of design conservatism in the sense of quadratic performance by utilizing the uncertainty structure. The class of uncertainty treated includes all the form of additive real parameter uncertainty, which has the multiple rank structure. To handle the structure of uncertainty, the scaling matrix with block diagonal structure is introduced. By changing the scaling matrix, all the possible set of uncertainty structures can be represented. Modified algebraic Riccati equation (MARE) is newly proposed to obtain a robust feedback control law, which makes the quadratic cost finite for an arbitrary scaling matrix. The remaining design freedom, that is, the scaling matrix is used for minimizing the upper bound of the quadratic cost for all possible set of uncertainties within the given bounds. A design example is shown to demonstrate the simplicity and the effectiveness of proposed method.