• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1098-1100
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• 2005

The floorplanning problem is an essential design step in VLSI layout design and it is how to place rectangular modules as density as possible. And then, as the DSM advances, the VLSI chip becomes more congested even though more metal layers are used for routing. Usually, a VLSI chip includes several buses. As design increases in complexity, bus routing becomes a heavy task. To ease bus routing and avoid unnecessary iterations in physical design, we need to consider bus planning in early floorplanning stage. In this paper, we propose a floorplanning method for topological constraint consisting of bus constraint and memory constraint. The proposed algorithms based on Genetic Algorithm(GA) is adopted a sequence pair. For selection control, new objective functions are introduced for topological constraint. Studies on floor planning and cell placement have been reported as being applications of GA to the LSI layout problem. However, no studies have ever seen the effect of applying GA in consideration of topological constraint. Experimental results show improvement of bus and memory constraint.

• Korean Journal of Computational Design and Engineering
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• v.3 no.4
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• pp.211-222
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• 1998

Parametric design is an important modeling paradigm in CAD/CAM applications, enabling efficient design modifications and variations. One of the major issues in parametric design is to develop a geometric constraint solver that can handle a large set of geometric configurations efficiently and robustly. In this appear, we propose a new approach to geometric constraint solving that employs a graph-based method to solve the ruler-and-compass constructible configurations and a numerical method to solve the ruler-and-compass non-constructible configurations, in a way that combines the advantages of both methods. The geometric constraint solving process consists of two phases: 1) planning phase and 2) execution phase. In the planning phase, a sequence of construction steps is generated by clustering the constrained geometric entities and reducing the constraint graph in sequence. in the execution phase, each construction step is evaluated to determine the geometric entities, using both approaches. By combining the advantages of the graph-based constructive approach with the universality of the numerical approach, the proposed approach can maximize the efficiency, robustness, and extensibility of geometric constraint solver.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.7
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• pp.619-624
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• 2011

This paper presents a controller design method for a robust control problem with multiple constraints using genetic algorithms and LMI design method. A robust $H_{\infty}$ constraint with loop shaping and pole placement is used to address disturbance attenuation with error limits and desired transient specifications, in spite of the plant uncertainties and disturbances. In addition, a loop gain constraint is considered so as not to enlarge the loop gain unnecessarily. The robust $H_{\infty}$ constraint and pole placement constraint can be expressed in terms of two matrix inequalities and the loop gain constraint can be considered as an objective function so that genetic algorithms can be applied. Accordingly, a robust controller can be obtained by integrating genetic algorithms with LMI approach. The proposed controller design method is applied to a track-following system of an optical disk drive and is evaluated through simulation results.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.589-594
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• 1997

We have already presented the constraint satisfaction algorithm which could solve the losed loop problem in constraint network by using local constraint propagation, variable elimination and constraint modularization. With this algorithm, we have implemented a knowledge-based system (intelligent CAD) for supporting machine design interactively. In this paper, we present newer constraint satisfaction algorithm which can solve inequalities or under-constrained problems in constraint network, interactively and efficiently. This algorithm is a hybrid type of using both declarative description (constraint represention) and optimization algorithm (Simulated Annealing), simultaneously. The under-constrained problems are represented by constraint networks and satisfied completely with this algorithm. The usefulness of our algorithm will be illustrated by the application to a gear design.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.9
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• pp.116-123
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• 1997

We have already presented the constraint satisfaction algorithm which could solve the closed loop porblem in constraint network by using local constraint propagation, variable elimination and constraint modularization. With this algorithm, we have implemented a knowledge-based system (intelligent CAD) for supporting machine design interactively. In this paper, we present newer constraint satisfaction algorithm which can solve inequalities or under-constrained problems in constraint network, interactively and effi- ciently. This algorithm is a hybrid type of using both declarative description (constraint representation) and optimization algorithm (Simulated Annealing), simultaneously. The under-constrained problems are represented by constraint networks and satisfied completely with this algorithm. The usefulness of our algorithm will be illustrated by the application to a gear design.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.1
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• pp.41-46
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• 2012

In this paper, An efficient circuit design algorithm considering constraint is proposed. The proposed algorithm sets up in time constraint and area constraint, power consumption constraint for a circuit implementation. First, scheduling process for time constraint. Select the FU(Function Unit) which is satisfied with time constraint among the high level synthesis results. Analyze area and power consumption of selected FUs. Constraint set for area and power constraint. Device selection to see to setting condition. Optimization circuit implementation in selected device. The proposed algorithm compared with [7] and [8] algorithm. Therefore the proposed algorithm is proved an efficient algorithm for optimization circuit implementation.

• Korean Journal of Computational Design and Engineering
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• v.6 no.2
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• pp.78-88
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• 2001

In order to adopt feature-based parametric modeling, CAD/CAM applications must have a geometric constraint solver that can handle a large set of geometric configurations efficiently and robustly. In this paper, we describe a graph constructive approach to solving geometric constraint problems. Usually, a graph constructive approach is efficient, however it has its limitation in scope; it cannot handle ruler-and-compass non-constructible configurations and under-constrained problems. To overcome these limitations. we propose an algorithm that isolates ruler-and-compass non-constructible configurations from ruler-and-compass constructible configurations and applies numerical calculation methods to solve them separately. This separation can maximize the efficiency and robustness of a geometric constraint solver. Moreover, the solver can handle under-constrained problems by classifying under-constrained subgraphs to simplified cases by applying classification rules. Then, it decides the calculating sequence of geometric entities in each classified case and calculates geometric entities by adding appropriate assumptions or constraints. By extending the clustering types and defining several rules, the proposed approach can overcome limitations of previous graph constructive approaches which makes it possible to develop an efficient and robust geometric constraint solver.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.4
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• pp.720-730
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• 2002

Automated design of large structures requires efficient and accurate optimization algorithms because of a large number of design variables and design constraints. The objective of this study is to examine the characteristics of the Kreisselmeier -Steinhauser envelope function and to investigate va tidily of accumulating constraint functions into a small number of constraint functions or even into a single constraint function. The commercial package DOT is adopted as a local optimizer. The optimum results using the envelope function are compared with those of the conventional method for a number of numerical examples and the differences between them are shown to be negligible.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.23 no.4
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• pp.356-364
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• 2013

This paper presents a tracking gain-up controller design method to control effectively the vibration of tracking actuator caused by external shocks and remaining velocity after seek control. A pole placement constraint is considered to assure a desired transient response against the vibration of tracking actuator. A loop gain-up constraint is introduced to hold the tracking gain-up loop gain and control bandwidth within allowable bounds. The pole placement constraint is expressed by a matrix inequality and the loop gain-up constraint is considered as an objective function so that genetic algorithm can be applied. Finally, a tracking gain-up controller is obtained by integrating a genetic algorithm with LMI design approach. The proposed tracking gain-up controller design method is applied to the track-following system of a DVD recording device and its effectiveness is evaluated through the experimental results.

• Journal of the Korean Society for Precision Engineering
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• v.33 no.8
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• pp.669-681
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• 2016

Mechanical designers often make mistakes that result in unwanted over-constraints, causing difficulty in assembly operations and residual stress due to interference among parts. This study is concerned with detection and elimination of over-constraints. Screw theory is a general method that is used for constraint analysis of an assembly and motion analysis of a mechanism. Mechanical assemblies with plane-plane, pin-hole, and pin-slot constraint pairs are analyzed using screw theory to illustrate its utility. As a real-world problem, a ball valve design is analyzed using the same method, and several unwanted over-constraints are detected. Elimination measures are proposed. Nominal dimensions of some parts are adjusted, and dimensions and tolerances of the pins and holes are modified using the virtual condition boundary concept. The revised design is free of over-constraints. General procedure for applying screw theory to constraint analysis is established and demonstrated; it will contribute to improving quality of assembly designs.