• Nuclear Engineering and Technology
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• v.55 no.5
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• pp.1838-1854
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• 2023

This paper presents a hybrid algorithm to solve the multi-objective path planning (MOPP) problem for mobile robots in a static nuclear accident environment. The proposed algorithm mimics a real nuclear accident site by modeling the environment with a two-layer cost grid map based on geometric modeling and Monte Carlo calculations. The proposed algorithm consists of two steps. The first step optimizes a path by the hybridization of improved ant colony optimization algorithm-modified A^* (IACO-A^*) that minimizes path length, cumulative radiation dose and energy consumption. The second module is the high radiation dose rate avoidance strategy integrated with the IACO-A^* algorithm, which will work when the mobile robots sense the lethal radiation dose rate, avoiding radioactive sources with high dose levels. Simulations have been performed under environments of different complexity to evaluate the efficiency of the proposed algorithm, and the results show that IACO-A^* has better path quality than ACO and IACO. In addition, a study comparing the proposed IACO-A^* algorithm and recent path planning (PP) methods in three scenarios has been performed. The simulation results show that the proposed IACO-A^* IACO-A^* algorithm is obviously superior in terms of stability and minimization the total cost of MOPP.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.7
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• pp.1110-1119
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• 2003

This paper deals with the synthesis of the 3-dimensional grasp planning for unknown objects. Previous studies have many problems, which the estimation time for finding the grasping points is much long and the analysis used the not-perfect 3-dimensional modeling. To overcome these limitations in this paper new algorithm is proposed, which algorithm is achieved by two steps. First step is to find the whole 3-dimensional geometrical modeling for unknown objects by using stereo matching. Second step is to find the optimal grasping points for unknown objects by using the neural network trained by the result of optimization using genetic algorithm. The algorithm is verified by computer simulation, comparing the result between neural network and optimization.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.5
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• pp.2536-2543
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• 2013

In this paper, we proposed the modeling in one zone buildings and the energy efficient temperature control algorithm using particle swarm optimization (PSO). A control horizon switching method with PSO is used for optimal control, and the TOU tariff is included to calculate the energy costs. Simulation results show that the reductions of energy cost and peak power can be obtained using proposed algorithms.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1101-1106
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• 2005

The purpose of this study was to develop a process management system to manage ingot fabrication and the quality of the ingot. The ingot is the first manufactured material of wafers. Operating data (trace parameters) were collected on-line but quality data (measurement parameters) were measured by sampling inspection. The quality parameters were applied to evaluate the quality. Thus, preprocessing was necessary to extract useful information from the quality data. First, statistical methods were employed for data generation, and then modeling was accomplished, using the generated data, to improve the performance of the models. The function of the models is to predict the quality corresponding to the control parameters. The dynamic polynomial neural network (DPNN) was used for data modeling that used the ingot fabrication data.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.33A no.7
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• pp.156-161
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• 1996

Accurate equivalent circuit modeling using multi-circuit optimization has been perfomred for detemining small-signal model of AlGaAs/GaAs HBTs. Three equivalent circuits for a cutoff biasing and two active biasing at different curretns are optimized simultaneously to fit gheir S parameters under the physics-based constrain that current-dependent elements for one of active circuits are connected to those for another circit multiplied by the ratio of two currents. The cutoff mode circuit and the physical constrain give the advantage of extracting physically acceptable parameters, because the number of unknown variables. After this optimization, three ses of optimized model S-parameters agree well with their measured S-parameters from 0.045 GHz to 26.5GHz.

• Korean Journal of Computational Design and Engineering
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• v.4 no.2
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• pp.127-138
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• 1999

For reverse engineering, curves and surfaces are modeled for new products by interpolating the digitized data points. But there are many measuring or deviation errors. Therefore, it is important to handle errors during the curve or surface modeling. If the errors are ignored, designer could get undesirable results. For this reason, fairing procedure with the aesthetics criteria is necessary in computer modeling. This paper presents methods of 3D NURBS curve fairing. The techniques are based on automatic repositioning of the digitized dat points or the NURBS curve control points by a constrained nonlinear optimization algorithm. The objective function is derived variously by derived curved. Constraints are distance measures between the original and the modified digitized data points. Changes I curve shape are analyzed by illustrations of curve shapes, and continuous plotting of curvature and torsion.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.5 s.176
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• pp.1166-1174
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• 2000

In this paper, we introduce a positioner based on magnetic levitation to eliminate the friction which is the most severe effect to limit high resolution on the micro level. Differently from existing electromagnetic device, the proposed positioner consists of air core solenoid and permanent magnet. Although the combination produces small magnetic force, it is suitable for realizing micro motion repeatedly without the accumulation of error because there is no hysteresis caused by ferromagnetic materials, no eddy current loss, no flux saturation. First, the approximate modeling of stiffness and damping effects between the magnetic elements is made and verified experimentally. Then, we have formulated the dynamic equation of one d.o.f magnetic levitation positioner using linear perturbation method and discussed the necessity of optimization for the chief design parameters to maximize the stability performance.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.624-627
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• 1992

Mathematical modeling is majorly divided into three parts: the derivation of models, the fitting of models to data, and the simulation of data from models. This paper focuses on the parameter optimization which is necessary for the fitting of models to data. The method of simulated annealing(SA) is a technique that has recently attracted significant attention as suitable for optimization problem of very large scale. If the temperature is too high, then some of the structure created by the heuristic will be destroyed and unnecessary extra work will be done. If it is too low then solution is lost, similar to the case of a quenching cooling schedule in the SA phase. In this study, therfore, we propose a technique of determination of the starting temperature and cooling schedule for SA phase.

• Journal of Hydrogen and New Energy
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• v.24 no.5
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• pp.373-385
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• 2013

To obtain higher power efficiency of Residential Power Generation system(RPG), it is needed to operate system on optimized stoichiometric ratios of fuel and air. Stoichiometric ratios of fuel/air are closely related to efficiency of stack, reformer and power consumption of Balance Of Plant(BOP). In this paper, optimizing stoichiometric ratios of fuel/air are conducted through systematic experiments and modeling. Based on fundamental principles and experimental data, constraints are chosen. By implementing these optimum values of stoichiometric ratios, power efficiency of the system could be maximized.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.14 no.3
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• pp.241-245
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• 2001

In this paper, we present parameter optimization technique for GaAs/AlGaAs multiple quantum well avalanche photodiodes used for image capture mechanism in high-definition system. Even under flawless environment in semiconductor manufacturing process, random variation in process parameters can bring the fluctuation to device performance. The precise modeling for this variation is thus required for accurate prediction of device performance. The precise modeling for this variation is thus required for accurate prediction of device performance. This paper will first use experimental design and neural networks to model the nonlinear relationship between device process parameters and device performance parameters. The derived model was then put into genetic algorithms to acquire optimized device process parameters. From the optimized technique, we can predict device performance before high-volume manufacturign, and also increase production efficiency.