• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.12
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• pp.1926-1932
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• 2001

In this second part of the paper, the automatic mesh generation and remeshing algorithm using bubble packing method is applied to the nonlinear problem. The remeshing/refinement procedure is necessary in the large deformation process especially because the mesh distortion deteriorates the convergence and accuracy. To perform the nonliear analysis, the transfer of state variables such as displacement and strain is added to the algorithm of Part 1. The equilibrium equation based on total Lagrangian formulation and elasto-viscoplastic model is used. For the numerical experiment, the upsetting process including the contact constraint condition is analyzed by two refinement criteria. And from the result, it is addressed that the present algorithm can generate the refined meshes easily at the largely deformed area with high error.

• Journal of Mechanical Science and Technology
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• v.19 no.spc1
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• pp.364-370
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• 2005

A stable walking pattern generation method for a biped robot is presented in this paper. In general, the ZMP (zero moment point) equations, which are expressed as differential equations, are solved to obtain a stable walking pattern. However, the number of differential equations is less than that of unknown coordinates in the ZMP equations. It is impossible to integrate the ZMP equations directly since one or more constraint equations are involved in the ZMP equations. To overcome this difficulty, DAE (differential and algebraic equation) solution method is employed. The proposed method has enough flexibility for various kinematic structures. Walking simulation for a virtual biped robot is performed to demonstrate the effectiveness and validity of the proposed method. The method can be applied to the biped robot for stable walking pattern generation.

• Proceedings of the KIEE Conference
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• 1997.07c
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• pp.1060-1063
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• 1997

A new generation planning algorithm considering environmental constraint by using fuzzy technique is developed. This algorithm has a new formula which can consider environmental constraints and an effective solving method which has newly developed fuzzy dual procedure. By using this algorithm, economic generation planning considering environmental constraints can be scheduled. The usefulness of this method is verified by applying it to the test system.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.8
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• pp.831-840
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• 1992

This paper presents an efficient short-term generation scheduling method using a rule-based expert/consulting system approach to assist electric energy system operators and planners. The expert system approach is applied to improve the Dynamic Programming(DP) based generation scheduling algorithm. In the selection procedure of the feasible combinations of generating units at each stage, automatic consulting on the manipulation of several constraints such as the minimum up time, the minimum down time and the maximum running time constraints of generating units will be performed by the expert/consulting system. In order to maximize the solution feasibility, the aforementioned constraints are controlled by a rule-based expert system, that is, instead of imposing penalty cost to those constraint violated combinations, which sometimes may become the very reason of no existing solution, several constraints will be manipulated within their flexibilities using the rules and facts that are established by domain experts. In this paper, for the purpose of implementing the consulting of several constraints during the dynamic process of generation scheduling, an expert system named STGSCS is developed. As a building tool of the expert system, C Language Integrated Production System(CLIPS) is used. The effectiveness of the proposed algorithm has been demonstrated by applying it to a model electric energy system.

• The Journal of Engineering Research
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• v.6 no.1
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• pp.5-14
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• 2004

Finding a solution to a constraint satisfaction problem requires choosing values for variables so as to satisfy the constraints of the problem. A constraint is simply a logical relation among several unknowns (or variables), each taking a value in a given domain. Conventional constraint-based scheduling systems are not enough to satisfy the all constraints because there are conflicts between them. In this paper, we propose a method for interactive scheduling, which have two major problems: first, it is hard to satisfy concretely all various kinds of constraints, and second, the search space is extremely large and requires a long execution time. To solve the above problems, we introduce the Interactive Scheduling System (ISS) that interacts with the user to exchange suggestions each other. Our system is performed in two steps: knowledge base generation of an initial assignment and iterative improvement with the user(host or internet client) to satisfy the constraints. Applying our system, we actually constructed timetables for our university, where the scheduling time is considerably reduced.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.361-364
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• 1997

The re-enty guidance design involves trajectory optimization, generation of a reference drag acceleration profile with the satisfaction of trajectory constraints. This reference drag acceleration profile can be considered as the reference trajectory. This paper proposes the atmospheric re-entry system which is composed of longitudinal, later and range control. This paper shows the a performance of a re-entry guidance and control system using feedback linearization control and predictive control.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.861-864
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• 1993

This research provides the results of a trial to generate the chaos by using nonlinear function constructed by fuzzy inference rules. The chaos generation function or chaotic behavior can be obtained by using Takagi-Sugeno fuzzy model with some constraint of the relationship of its parameters. Two examples are shown in this research. The first is simple example that construct of logistic image by fuzzy model. The second is more complicated one that provide the chaotic time series by non-linear autoregression based on fuzzy model. Simulated results are shown in these examples.

• Journal of information and communication convergence engineering
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• v.8 no.2
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• pp.191-196
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• 2010

This paper presents automatic generation of robot motion using posture template in physical training system. In this system, we define a human-like generic template with two angles, then, we generate robot motion that has used angle data of the created template. The angle data is transformed automatically to the most similar motion. This is achieved by suitable expressions for robot specification. The expressions intend to differences of angle measurement on X,Y,Z planes and DOF constraint. We choose several postures and create generic templates for chosen postures. Robot motions are also generated from generic templates by expressions.

• Proceedings of the KIEE Conference
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• 2005.07a
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• pp.274-276
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• 2005

Stability is an important constraint in powr system operation. A new methodology that reduces the need for repeated simulation to determine a transiently secure operating point is presented. at cntingency, critical generator is limited generation to prevent rotor accelation until system is secured. when energh margin is zero, generation is degermined Implementation issues and simulation results are discussed in th context of a 10-bus system.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.05a
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• pp.31-33
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• 2007

Devising an efficient one-pass frequent pattern mining algorithm has been an issue in data mining research in recent past. Pattern growth algorithms like FP-Growth which are found more efficient than candidate generation and test algorithms still require two database scans. Moreover, FP-growth approach requires rebuilding the base-tree while mining with different support counts. In this paper we propose an item-based tree, called I-Tree that not only efficiently mines frequent patterns with single database scan but also provides multiple mining scopes with multiple support thresholds. The 'build-once-mine-many' property of I-Tree allows it to construct the tree only once and perform mining operation several times with the variation of support count values.