• 한국원자력학회:학술대회논문집
• /
• 한국원자력학회 1996년도 춘계학술발표회논문집(1)
• /
• pp.380-385
• /
• 1996

The genetic algorithm(GA) is applied to the design of the nuclear power control system. The reactor control system model is described in the LQR configuration. The LQR system order is increased to make the tracking system. The key parameters of the design are weighting matrices, and these are usually determined through numerous simulations in the conventional design. To determine the more objective and optimal weightings, the improved GA is applied. The results show that the weightings determined by the GA yield the better system responses than those obtained by tile conventional design method.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2002년도 하계학술대회 논문집 A
• /
• pp.320-326
• /
• 2002

Distribution system loss minimization re-configuration is 0-1 planning problem, and the number of combinations requiring searches is extremely large when dealing with typical system scales. For this reason, the application of a genetic algorithm (GA) seems attactive to solve this problem. Although Genetic algorithms are a type of random number search method, they incorporate a multi-point search feature and are therefore superior to one-point search techniques. The efficiency of GAs for solving large combinational problem has received wide attention. Further, parallel searching can be performed and the optimal solution is more easily reached. In this paper, for improving GA convergence characteristics in the distribution system loss minimization re-configeration problem, a chromosome "Limited Life" concept is intro duced. Briefly, considering the population homogenization and genetic drift problems, natural selection is achieved by providing this new concept, in addition to natural selection by fitness. This is possible because individuals in a population have an age value. Simulations were carried out using a model system to check this method's validity.

• 한국지능정보시스템학회:학술대회논문집
• /
• 한국지능정보시스템학회 1999년도 춘계공동학술대회-지식경영과 지식공학
• /
• pp.145-154
• /
• 1999

An intelligent system embedded with multiple sources of knowledge may provide more robust intelligence with highly ill structured problems than the system with a single source of knowledge. This paper proposes th hybrid knowledge integration mechanism that yields the cooperated knowledge by integrating expert, user, and machine knowledge within the fuzzy logic-driven framework, and then refines it with a genetic algorithm (GA) to enhance the reasoning performance. The proposed knowledge integration mechanism is applied for the prediction of Korea stock price index (KOSPI). Empirical results show that the proposed mechanism can make an intelligent system with the more adaptable and robust intelligence.

• Journal of Advanced Marine Engineering and Technology
• /
• 제24권2호
• /
• pp.63-71
• /
• 2000

This paper deals with a systematic approach to GA-PI controller design for static VAR compensator(SVC) using genetic algorithm(GA) to improve system stability. Genetic algorithms(GAs) are search algorithms based on the mechanics of natural selection and natural genetics. To verify the validity of the proposed method, investigated damping ratio of the eigenvalues of the electro-mechanical modes system with and without SVC. Also, we considered dynamic response of terminal speed deviation and terminal voltage deviation by applying a power fluctuation at heavy load, normal load and light to verify the robustness of the proposed. Thus, we proved usefulness of GA-PI controller design to improve the stability of single machine-bus with SVC system.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2002년도 하계학술대회 논문집 A
• /
• pp.295-297
• /
• 2002

In this study, Genetic Algorithm(GA) is applied for voltage and reactive power control in power system. In power system, switched shunt capacitors are used to improve the voltage profile and to reduce power losses. There are many switched shunt capacitors in power system. Therefore, it is necessary to coordinate these switched shunt capacitors. A Genetic Algorithm(GA) is used to find optimal coordination of switched shunt capacitors in power system. The effectiveness of the proposed approach is demonstrated in KEPCO's power system.

• 한국지능시스템학회논문지
• /
• 제8권5호
• /
• pp.61-71
• /
• 1998

Genetic Algorithm(GA) is a method of approaching optimization problems by modeling and simulating the biological evolution. GA needs large time-consuming, so ti had better do on a parallel computer architecture. Our proposed system has a VLSI-oriented interconnection network, which is constructed from a viewpoint of fractal geometry, so that self-similarity is considered in its configuration. The approach to Parallel Genetic Algorithm(PGA) on our proposed system is explained, and then, we construct the classifier system such that the set of samples is classified into weveral classes based on the features of each sample. In the process of designing the classifier system, We have applied PGA to the Traveling Salesman Problem and classified the sample set in the Euclidean space into several categories with a measure of the distance.

• 한국생산제조학회지
• /
• 제26권3호
• /
• pp.313-319
• /
• 2017

This study presents a genetic algorithm (GA) to design a PID controller systematically for an inchworm operated by piezoelectric actuators. The performance index considering overshoot and settling time is adopted to search an optimal PID gain using GA. The piezoelectric actuator shows nonlinear characteristics including hysteresis and residual displacement. The PID feedback system combined with an integrator is used to improve the ability of tracking the complex input signals and suppressing the steady state error. The PID controller tuned by GA can track the various motion contours effectively. However, the PID controller shows an improper residual vibration under the application of high-frequency square input. The input shaper combined with the feedback system can overcome this limitation of the PID controller.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 1997년도 추계학술대회 논문집 학회본부
• /
• pp.119-121
• /
• 1997

This paper suggests a design method of the robust model following PD control system using genetic algorithm. This PD control system is designed by applying genetic algorithm with reference model to the optimal determination of proportional and derivative gains that are given by PD servo controller. These proportional and derivative gains are optimized simultaneously in the search domain guaranteeing the robust stability of closed-loop system satisfying different stability margins. The effectiveness of this PD control system is verified by computer simulation.

• 대한전기학회논문지:전력기술부문A
• /
• 제49권3호
• /
• pp.118-123
• /
• 2000

This paper presents an efficient algorithm for loss reduction and load balancing by sectionalizing switch operation in large scale distribution system of radial type. We use Genetic algorithm and Kruskal algorithm to solve distribution system reconfiguration. Genetic algorithm is used to minimize objective function including loss and load balancing items. Kruskal algorithm is used to satisfy the radial condition of distribution system. The experimental results show that the proposed method has the ability to search a good solution regardless of initial configuration and size of system.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 1998년도 추계학술대회 논문집 학회본부A
• /
• pp.326-328
• /
• 1998

This paper presents an optimal fuzzy power system stabilizer to damp out low frequency oscillation. The fuzzy logic controllers has been applied to a power system stabilizing controllers. But the design of a fuzzy logic power system stabilizer relies on empirical and heuristic knowledge of human experts as well as many trial-and-errors in general. This paper presents the optimal design method of the fuzzy logic stabilizer using the genetic algorithm, which is the optimization method based on the mechanics of natural selection and natural genetics. The proposed method tunes the parameters of the fuzzy logic stabilizer in order to minimize the consuming time during the design process. In this paper, the proposed method tunes the shape of membership function of the fuzzy variables. The proposed system is applied to the one-machine infinite-bus model of a power system. Through the case study, the efficiency of the fuzzy stabilizing controller tuned by genetic algorithm is verified.