• The Transactions of the Korean Institute of Electrical Engineers P
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• v.52 no.2
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• pp.74-80
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• 2003

In this paper, a robust two-degree-of-freedom(TDF) the speed control system using $H_{\infty}$ optimization method and real genetic algorithm is proposed for the robust stability and the robust performance in dc servo motor system. This control system composed of feedback and feedforward controller. The feedback(FB) controller with $H_{\infty}$ optimization method is designed for real genetic algorithm that is model matching problem using mixed sensitivity function. The feedforward(FF) controller with $H_{\infty}$optimization method is minimized the error between transfer function of the optimal model and the overall transfer function. The proposed robust two-degree-of-freedom speed control system is simulated to the dc servo motor. By the simulation, feedback controller can obtain the robust stability property and feedforward controller can obtain the robust performance property under modelling error. The performance of the dc servo motor is analyzed by the experiment setting. The validity of the proposed method is verified through being compared with pid(proportional integrated differential)control system design method for the dc servo motor.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.58 no.4
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• pp.359-366
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• 2022

In this study, the load fluctuation of the main engine is considered to be a disturbance for the jacket coolant temperature control system of the low-speed two-stroke main diesel engine on the ships. A nonlinear PID temperature control system with satisfactory disturbance rejection performance was designed by rapidly transmitting the load change value to the controller for following the reference set value. The feed-forwarded load fluctuation is considered the set points of the dual loop control system to be changed. Real-coded genetic algorithms were used as an optimization tool to tune the gains for the nonlinear PID controller. ITAE was used as an evaluation function for optimization. For the evaluation function, the engine jacket coolant outlet temperature was considered. As a result of simulating the proposed cascade nonlinear PID control system, it was confirmed that the disturbance caused by the load fluctuation was eliminated with satisfactory performance and that the changed set value was followed.

• Journal of Korean Port Research
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• v.14 no.2
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• pp.155-163
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• 2000

A discrete system has interpreted by using the network model, and PERT network is one of these methods. For the purpose of analysing the real system, it is necessary to measure the parameter of the real system. And system identification problem is to assume the parameter of a real system when we get to know the system model, the input data and output data. System identification method has been only developed to a system of which a structure has expressed a differential equation or a polynomial expression. But it has been scarcely developed yet in that case of network model. The aim of this paper is to examine a changes when new system is introduced to the present system. The changes are as follows : how the present system will be changed, when the changes will be happened. In this paper, genetic algorithm is used to assume the parameter.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 1999.10a
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• pp.101-108
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• 1999

A discrete system has interpreted by using the network model, and PERT network is one of these methods. For the purpose of analysing the real system. it is necessary to measure the parameter of the real system. And system identification problem is to assume the parameter of a real system when we get to know the system model, the input data and output data. System identification method has been only developed to a system of which a structure has expressed a differential equation or a polynomial expression. But it has been scarcely developed yet in that case of network model. The aim of this paper is to examine a changes when new system isn introduced to the present system, The changes are as follows: how the present system will be changed, when the changes will be happened. In this paper, genetic algorithm is used to assume the parameter.

• Journal of Intelligence and Information Systems
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• v.11 no.1
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• pp.191-205
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• 2005

This paper presents a novel product recommender system as a tool fur differentiated marketing service of online shopping malls. Ihe proposed model uses genetic algorithnt one of popular global optimization techniques, to construct a personalized product recommender systen The genetic algorinun may be useful to recommendation engine in product recommender system because it produces optimal or near-optimal recommendation rules using the customer profile and transaction data. In this study, we develop a prototype of WeLbased personalized product recommender system using the recommendation rules fi:om the genetic algorithnL In addition, this study evaluates usefulness of the proposed model through the test fur user satisfaction in real world.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.10
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• pp.556-564
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• 2004

This paper presents an application of parallel Genetic Algorithm-Tabu Search(GA-TS) algorithm to search an optimal solution of a reconfiguration in distribution system. The aim of the reconfiguration of distribution systems is to determine switch position to be opened for loss minimization in the radial distribution systems, which is a discrete optimization problem. This problem has many constraints and very difficult to solve the optimal switch position because it has many local minima. This paper develops parallel GA-TS algorithm for reconfiguration of distribution systems. In parallel GA-TS, GA operators are executed for each processor. To prevent solution of low fitness from appearing in the next generation, strings below the average fitness are saved in the tabu list. If best fitness of the GA is not changed for several generations, TS operators are executed for the upper 10% of the population to enhance the local searching capabilities. With migration operation, best string of each node is transferred to the neighboring node aster predetermined iterations are executed. For parallel computing, we developed a PC-cluster system consisting of 8 PCs. Each PC employs the 2 GHz Pentium Ⅳ CPU and is connected with others through ethernet switch based fast ethernet. To show the usefulness of the proposed method, developed algorithm has been tested and compared on a distribution systems in the reference paper. From the simulation results, we can find that the proposed algorithm is efficient and robust for the reconfiguration of distribution system in terms of the solution qualify. speedup. efficiency and computation time.

• KIEE International Transactions on Power Engineering
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• v.5A no.2
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• pp.116-124
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• 2005

This paper presents an application of the parallel Genetic Algorithm-Tabu Search (GA- TS) algorithm, and that is to search for an optimal solution of a reconfiguration in distribution systems. The aim of the reconfiguration of distribution systems is to determine the appropriate switch position to be opened for loss minimization in radial distribution systems, which is a discrete optimization problem. This problem has many constraints and it is very difficult to solve the optimal switch position because of its numerous local minima. This paper develops a parallel GA- TS algorithm for the reconfiguration of distribution systems. In parallel GA-TS, GA operators are executed for each processor. To prevent solution of low fitness from appearing in the next generation, strings below the average fitness are saved in the tabu list. If best fitness of the GA is not changed for several generations, TS operators are executed for the upper 10$\%$ of the population to enhance the local searching capabilities. With migration operation, the best string of each node is transferred to the neighboring node after predetermined iterations are executed. For parallel computing, we developed a PC-cluster system consisting of 8 PCs. Each PC employs the 2 GHz Pentium IV CPU and is connected with others through switch based rapid Ethernet. To demonstrate the usefulness of the proposed method, the developed algorithm was tested and is compared to a distribution system in the reference paper From the simulation results, we can find that the proposed algorithm is efficient and robust for the reconfiguration of distribution system in terms of the solution quality, speedup, efficiency, and computation time.

• Journal of Embryo Transfer
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• v.33 no.4
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• pp.245-254
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• 2018

Pigs are considered as optimal donor animal for the successful xenotransplantation. To increase the possibility of clinical application, genetic modification to increase compatibility with human is an important and essential process. Genetic modification technique has been developed and improved to produce genetically modified pigs rapidly. CRISPR/Cas9 system is widely used in various fields including the production of transgenic animals and also can be enable multiple gene modifications. In this study, we developed new gene targeting vector and enrichment system for the rapid and efficient selection of genetically modified cells. We conducted co-transfection with two targeting vectors for simultaneous inactivation of two genes and enrichment of the genetically modified cells using MACS. After this efficient enrichment, genotypic analysis of each colony showed that colonies which have genetic modifications on both genes were confirmed with high efficiency. Somatic cell nuclear transfer was conducted with established donor cells and genetically modified pigs were successfully produced. Genotypic and phenotypic analysis of generated pigs showed identical genotypes with donor cells and no surface expression of ${\alpha}$-Gal and HD antigens. Furthermore, functional analysis using pooled human serum revealed dramatically reduction of human natural antibody (IgG and IgM) binding level and natural antibody-mediated cytotoxicity. In conclusion, the constructed vector and enrichment system using MACS used in this study is efficient and useful to generate genetically modified donor cells with multiple genetic alterations and lead to an efficient production of genetically modified pigs.

• Journal of Power System Engineering
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• v.13 no.4
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• pp.68-73
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• 2009

The mathematical model has a different response character with the real system because this mathematical model has the modeling errors and the imprecise value of system's parameters. Therefore to find the value of system parameters as possible as near by real value in the model is necessary to design the controlled system. This study concern about the identification method to estimate the parameter for the magnetic bearing system with RCGA(Real Coded Genetic Algorithm). Firstly, we will get the mathematical model from the current amplifier circuit and the magnetic bearing system. Secondly we will get the step response data in this circuit and system. Finally, we will estimate the unknown parameter's value from the data.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.6
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• pp.656-666
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• 1999

In this paper, we design the optimal PD control system which has the robust performance. This PD control system is designed by applying genetic algorithm (GA) to the determination of proportional gain KP and derivative gain KD that are given by PD servo controller, to make the output of plant follow the output of reference model optimally. These proportional and derivatibe gains are simultaneously optimized in the search domain guaranteeing the robust performance of system. And, this PD control system is compared with $\mu$ -synthesis control system for the robust performance. The PD control system designed by the proposed method has not only the robust performance but also the better command tracking performance than that of the $\mu$ -synthesis control system. The effectiveness of this control system is verified by computer simulation.