• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.203-208
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• 1987

Design problem of output feedback controllers for discrete large scale systems using simplified model is investigated. It is shown that neglecting fast modes does not generally guarantee the stability of the closed loop system. In this paper, the design procedure is proposed to stabilize the system by minimizing a quadratic cost function for the simplified model and a measure of stability for the neglected fast model.

• Journal of the Korean Operations Research and Management Science Society
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• v.21 no.1
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• pp.1-17
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• 1996

There have been considerable researches for solving large-scale separable convex optimization ptoblems. In this paper we present a method for large-scale nonseparable smooth convex optimization problems with block-angular linear constraints. One of them is occurred in reconfiguration of the virtual path network which finds the routing path and assigns the bandwidth of the path for each traffic class in ATM (Asynchronous Transfer Mode) network [1]. The solution is approximated by solving a sequence of the block-angular structured separable quadratic programming problems. Bundle-based decomposition method [10, 11, 12]is applied to each large-scale separable quadratic programming problem. We implement the method and present some computational experiences.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.276-278
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• 1992

This paper presents a method of hierachical optimal control for time invariant large scale systems via Single Term Walsh Series. It is well known that the optimal control of a large scale system with quadratic performance criteria often involves the determination of time varying feedback gain matrix by solving the matrix Riccati differential equation, which is usually quite difficult. Therefore, in order to solve the problem, this paper is introduced to Single Term Walsh Series. The advantages of proposed method are simple and attractive for the control of large scale system in computation.

• International Journal of Aeronautical and Space Sciences
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• v.9 no.2
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• pp.79-86
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• 2008

High performance direct-iterative hybrid linear solver for large scale finite element problem is developed. Direct solution method is robust but difficult to parallelize, whereas iterative solution method is opposite for direct method. Therefore, combining two solution methods is desired to get both high performance parallel efficiency and numerical robustness for large scale structural analysis problems. Hybrid method mentioned in this paper is based on FETI-DP (Finite Element Tearing and Interconnecting-Dual Primal method) which has good parallel scalability and efficiency. It is suitable for fourth and second order finite element elliptic problems including structural analysis problems. We are using the hybrid concept of theses two solution method categories, combining the multifrontal solver into FETI-DP based iterative solver. Hybrid solver is implemented for our general structural analysis code, IPSAP.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2000.10a
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• pp.307-314
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• 2000

A parallel condensation algorithm for efficient dynamic analysis of three-dimensional large-scale structures is presented. The algorithm is developed for a user-friendly and cost effective high-performance computing system on a collection of Pentium processors connected via a 100 Mb/s Ethernet LAN. To harness the parallelism in the computing system effectively, a large-scale structure is partitioned into a number of substructures equal to the number of computers in the computing system Then, for reduction in the size of an eigenvalue problem the computations required for static condensation of each substructure is processed concurrently on each slave computer. The performance of th proposed parallel algorithm is demonstrated by applying to dynamic analysis of a three dimensional structure. The results show that how the parallel algorithm facilitates the efficient use of a small number of low-cost personal computers for dynamic analysis of large-scale structures.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.648-651
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• 2013

The information generated in large-scale and complex construction projects are transferred continuously and transformed into project products on the long span life cycle. Therefore, information flow management is related with the success of project directly. However, certain characteristics of large-scale and complex construction projects make the solving the problem more difficultly. Although several information retrieval systems support the information management system, it is not suitable to grasp information flows. Hence, we developed an information retrieval system specialized with the information flow based on a preceding research. The system consists of a relation-based database and the process information transferring relation inference application module. The system enables project managers to manage the entire project process more efficiently and each project member to work their own task being served the information flow retrieval results.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.8
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• pp.818-822
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• 2009

In this paper, we consider a decentralized observer design problem for fault detection in large-scaled linear time-invariant systems. Since the fault detection residual is desired to be sensitive on the fault, we use the H_ index performance criterion. Sufficient conditions for the existence of such an observer is presented in terms of linear matrix inequalities. Simulation results show the effectiveness of the proposed method.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.4
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• pp.223-230
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• 2015

As the Transportation Simplex Method of the general transportation problem are inapplicable to the large-scale unbalanced transportation problem, a commercialized linear programming package remains as the only viable means. There is, however, no method made available to verify the optimality of solutions attained by the package. This paper therefore proposes a simple heuristic algorithm to the large-scale unbalanced transportation problem. From a given problem of $31{\times}15$supply and demand areas, the proposed algorithm determines the number of demands areas for each supply area and executes on the latter in the ascending order of each of their corresponding demand areas. Next, given a single corresponding demand area, it supplies the full demand volume and else, it supplies first to an area of minimum associated costs and subsequently to the rest so as to meet the demand to the fullest extent. This initial optimal value is then optimized through an adjustment process whereby costs are minimized as much as possible. When tested on the $31{\times}15$cost matrix, the proposed algorithm has obtained an optimal result improved from the commercial linear programming package by 8.9%.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.11
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• pp.117-126
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• 2003

GA(genetic algorithm) has a powerful searching ability and is comparatively easy to use and to apply as well. By that reason, GA is in the spotlight these days as an optimization skill for mechanical systems.$^1$However, GA has a low efficiency caused by a huge amount of repetitive computation and an inefficiency that GA meanders near the optimum. It also can be shown a phenomenon such as genetic drifting which converges to a wrong solution.$^{8}$ These defects are the reasons why GA is not widdy applied to real world problems. However, the low efficiency problem and the meandering problem of GA can be overcomed by introducing parallel computation$^{7}$ and gray code$^4$, respectively. Standard GA(SGA)$^{9}$ works fine on small to medium scale problems. However, SGA done not work well for large-scale problems. Large-scale problems with more than 500-bit of sere's have never been tested and published in papers. In the result of using the SGA, the powerful searching ability of SGA doesn't have no effect on optimizing the problem that has 96 design valuables and 1536 bits of gene's length. So it converges to a solution which is not considered as a global optimum. Therefore, this study proposes ExpGA(experience GA) which is a new genetic algorithm made by applying a new probability parameter called by the experience value. Furthermore, this study finds the solution throughout the whole field searching, with applying ExpGA which is a optimization technique for the structure having genetic drifting by the standard GA and not making a optimization close to the best fitted value. In addition to them, this study also makes a research about the possibility of GA as a optimization technique of large-scale design variable problems.

• Journal of Electrical Engineering and Technology
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• v.1 no.4
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• pp.455-460
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• 2006

This paper presents the convergency property of the Auxiliary Problem Principle when it is applied to large-scale Optimal Power Flow problems with Distributed or Parallel computation features. The key features and factors affecting the convergence ratio and solution stability of APP are also analyzed.