• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.3
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• pp.247-256
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• 1999

In this paper, a methodology for optimal design of PID controller using the modified genetic algorithm has been proposed to improve the transient stability at system fault in HVDC transmission system, mathematical model preparation for stability analysis, and supplementary signal control by an optimal PID controller using the modified genetic algorithm(MGA). The propriety was verified through computer simulations regarding transient stability. It means that the application of MGA-PID controller in HVDC transmission system can contribute the propriety to the improvement of the transient stability in HVDC transmission system and the design of MGA-PID controller has been proved indispensible when applied to HVDC transmission system.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.51 no.7
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• pp.317-326
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• 2002

In this paper, a methodology for optimal PI supplementary controller using the modified genetic algorithm has been proposed to the oscillation damping in HDVC transmission system. These study processes are summarized as the formulation for load flow calculation in HVDC transmission system with SVC, the investigations on the basic control in HVDC system, the mathematical modeling for dynamic characteristics analyses, and the optimal design of MGA based PI controller generation the supplementary control signal of SVC. Its properties were verified through a series of computer simulations including dynamic stability. It means that the application of MGA-PI controller in HVDC transmission system can contribute the propriety to the improvement of the stability in HVDC transmission system and the design of MGA-OI controller has been proved indispensible when applied to HVDC transmission system.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.36C no.8
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• pp.54-61
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• 1999

In this paper, we apply one of modified Genetic Algorithms, a Multi-population Genetic Algorithm(MGA) that improves the genetic diversity to determine the fuzzy rule base and the shape of membership functions. The generation of the fuzzy rule base for fuzzy control, generally, depends on expert's experience. We suggest a new evaluation function to optimize fuzzy rule base. Simulation shows that the proposed method has good result.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.64 no.1
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• pp.14-17
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• 2015

This paper presents a analysis method for power system stability using a Modified Genetic-based Power System Stabilizer(MGPSS). The proposed MGPSS parameters are optimized using Modified Genetic Algorithm(MGA) in order to maintain optimal operation of generator under the various operating conditions. To improve the convergence characteristics, real variable string is adopted. The results tested on a single machine infinite bus system verify that the proposed controller has better power system stability than conventional controller.

• Proceedings of the KIEE Conference
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• 2007.11b
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• pp.165-167
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• 2007

This paper presents a analysis method for power system stability using a Modified Genetic-based Power System Stabilized(MGPSS). The proposed MGPSS parameters are optimized using Modified Genetic Algorithm(MGA) in order to maintain optimal operation of generator under the various operating conditions. To improve the convergence characteristics, real variable string is adopted. The results tested on a single machine infinite bus system verify that the proposed controller has better dynamic performance than conventional controller.

• 한국정보통신설비학회:학술대회논문집
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• 2005.08a
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• pp.115-119
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• 2005

In this paper, we propose a method that search the sweet spot of array antenna beam, and keep it for fast speed transmission in millimeter wave on single array antenna link. We use TDD(Time Division Duplex) as transfer method, and it transfers the control data of antenna. The proposed method is the modified genetic algorithm which selects a superior initial group through slave-processing in order to resolve the local solution of genetic algorithm. The efficiency of the proposed method is verified by means of simulations with white Gaussian noise and not on single array antenna link.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.717-720
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• 2007

This paper presents a novel scheme that quickly searches for the optimal direction of multiple directional antennas, and locks on to it for high-speed millimeter wavelength transmissions, when communications to another antenna directional are disconnected. The proposed method utilizes a modified genetic algorithm, which selects a superior initial group through preprocessing in order to solve the local solution in genetic algorithm. TDD (Time Division Duplex) is utilized as the transfer method and data controller for the antenna. Once the initial communication is completed for the specific number of individuals, no longer antenna's data will be transmitted nil each station processes GA in order to produce the next generation. After reproduction, individuals of the next generation become the data, and communication between each station is made again. In order to verify the effectiveness of the proposed system, simulation results of 1:1, 1:2, 1:5 directional antennas and experiment results of 1:1 directionalantennas confirmed the efficiency of the proposed method. The 16bit split is 8bit, but it has similar performance as 16bit gene.

• Nuclear Engineering and Technology
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• v.29 no.1
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• pp.68-77
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• 1997

The reactor power control system is described in the fashion of the order increased LQR system. To obtain the optimal state feedback gain vectors, the weighting matrix of the performance function should be determined. Since the contentional method has some limitations, stochastic searching methods are investigated to optimize the LQR weighting matrix using the modified genetic algorithm combined with the simulated annealing, a new optimizing tool named the hybrid MGA-SA is developed to determine the weighting parameters of the LQR system. This optimizing tool provides a more systematic approach in designing the LQR system. Since it can be easily incorporated with any forms of the cost function, it also provides the great flexibility in the optimization problems.