• 한국태양에너지학회:학술대회논문집
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• 한국태양에너지학회 2008년도 춘계학술발표대회 논문집
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• pp.61-67
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• 2008

In this paper proposed the solar tracking system to use a fuzzy based on PC in order to increase an output of the PV array. The solar tracking system operated two DC motors driving by signal of photo sensor. The control of dual axes is not an easy task due to nonlinear dynamics and unavailability of the parameters. Recently, artificial intelligent control of the fuzzy control, neural-network and genetic algorithm etc. have been studied. The fuzzy control made a nonlinear dynamics to well perform and had a robust and highly efficient characteristic about a parameter variable as well as a nonlinear characteristic. Hence the fuzzy control was used to perform the tracking system after comparing with error values of setting-up. nonlinear altitude and azimuth. In this paper designed a fuzzy controller for improving output of PV array and evaluated comparison with efficient of conventional PI controller. The data which were obtained by experiment were able to show a validity of the proposed controller.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 하계학술대회 논문집 A
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• pp.292-294
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• 2004

In this paper, we design the GA-fuzzy precompensator of a Power System Stabilizer for Thyristor Controlled Series Capacitor(TCSC-PSS) for enhancement of power system stability. Here a fuzzy precompensator is designed as a fuzzy logic-based precompensation approach for TCSC-PSS. This scheme is easily implemented simply by adding a fuzzy precompensator to an existing TCSC-PSS. And we optimize the fuzzy precompensator with a genetic algorithm for complements the demerit such as the difficulty of the component selection of fuzzy controller, namely, scaling factor, membership Auction and control rules. Simulation results show that the proposed control technique is superior to a conventional PSS in dynamic responses over the wide range of operating conditions and is convinced robustness and reliableness in view of structure.

• Industrial Engineering and Management Systems
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• 제12권4호
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• pp.306-316
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• 2013

The semiconductor industry has grown rapidly, and subsequently production planning problems have raised many important research issues. The reentrant flow-shop (RFS) scheduling problem with time windows constraint for harddisk devices (HDD) manufacturing is one such problem of the expanded semiconductor industry. The RFS scheduling problem with the objective of minimizing the makespan of jobs is considered. Meeting this objective is directly related to maximizing the system throughput which is the most important of HDD industry requirements. Moreover, most manufacturing systems have to handle the quality of semiconductor material. The time windows constraint in the manufacturing system must then be considered. In this paper, we propose a hybrid genetic algorithm (HGA) for improving chromosomes/offspring by checking and repairing time window constraint and improving offspring by left-shift routines as a local search algorithm to solve effectively the RFS scheduling problem with time windows constraint. Numerical experiments on several problems show that the proposed HGA approach has higher search capability to improve quality of solutions.

• 한국인터넷방송통신학회논문지
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• 제13권2호
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• pp.181-189
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• 2013

본 논문에서는 패턴 인식기를 설계하기 위하여 개별 입력 공간을 기반으로 한 퍼지 뉴럴 네트워크를 소개한다. 제안된 퍼지 뉴럴 네트워크는 각 입력 공간을 개별적으로 분할함으로서 네트워크를 구성한다. 규칙의 전반부는 개별적 입력 공간을 퍼지 분할하여 독립적으로 구성하고, 규칙의 후반부는 다항식으로서 표현된다. 퍼지 뉴럴 네트워크의 학습은 퍼지 규칙의 후반부에 있는 뉴런의 연결가중치를 조정함으로써 실현되고, 오류 역전파 알고리즘을 이용하여 실현한다. 또한, 제안한 네트워크의 파라미터를 최적화하기 위하여 실수 코딩 유전자 알고리즘을 이용한다. 마지막으로, 패턴 인식을 위한 실험 데이터를 이용하여 최적화된 패턴 인식기를 설계한다.

• 한국지능시스템학회논문지
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• 제14권4호
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• pp.445-450
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• 2004

본 논문은 실질적인 최적화 구조물의 설계를 위한 시스템에 대한 것으로 퍼지이론에 바탕을 둔 자동 유한요소 생성 망 기술과 계산 기하학적 기술, 해석코드 및 솔리드모델러를 시스템에 통합시켰다. 최적해 또는 만족해는 자동해석 시스템과 함께 탐색공간을 위한 유전자 알고리즘을 이용하여 자동적으로 탐색되어 진다. 또한, 유전자 알고리즘을 이용함으로써 본 설계 시스템은 다차원 해를 얻을 수 있다. 개발된 시스템은 터널전류에 바탕을 둔 마이크로 가속도계의 형상설계에 적용하였다.

• 제어로봇시스템학회논문지
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• 제5권5호
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• pp.600-613
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• 1999

This paper focuses on development of a performance manager for IEEE 802.4 token bus networks to serve large-scale integrated systems. In order to construct the management algorithm, the principles of fuzzy logic, genetic algorithm, and neural network have been combined to represent human knowledge and to imitate of human inference mechanism. Through the simulation experiments, it is shown that the proposed performance manager is capable of improving the network performance without a priori knowledge.

• 한국지능시스템학회논문지
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• 제6권3호
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• pp.25-36
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• 1996

기존의 RBF 신경망 및 퍼지 시스템을 고차원 입력 공간 위에서의 비선형 근사에 적용할 경우 은닉 노드의 수혹은 퍼지 IF-THEN 규칙의 수가 기하급수적으로 증가한다. 본 논문에서는 이러한 문제점을 개선하기 위해 반국소 유닛을 기본 요소로 하는 수목구조지능시스템을 제안하고, 이를 효과적으로 학습하기 위하여 수정 유전자 알고리즘 및 LMS 규칙에 기반을 둔 학습 알고리즘을 개발한다. 제안된 시스템에 대한 근사 능력 해석이 수행되고, 실험적 고찰을 통하여 개발된 방법론의 유용성이 입증된다.

• 한국공간구조학회논문집
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• 제14권2호
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• pp.87-94
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• 2014

In this study, a smart isolation platform has been developed for control of microvibration of high-technology facilities, such as semi-conductor plants and TFT-LCD plants. Previously, microvibration control performance of a smart base isolation system has been investigated. This study compared microvibration control performance of a smart isolation platform with that of conventional base isolation and fixed base. For this purpose, train-induced ground acceleration is used for time history analysis. An MR damper was used to compose a smart isolation platform. A fuzzy logic controller was used as a control algorithm and it was optimized by a multi-objective genetic algorithm. Numerical analysis shows that a smart isolation platform can effectively control microvibration of a high-technology facility subjected to train-induced excitation compared with other models.

• Journal of information and communication convergence engineering
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• 제5권1호
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• pp.35-41
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• 2007

In this paper, a modified Fuzzy C-Means (MFCM) algorithm is presented for nonlinear blind channel equalization. The proposed MFCM searches the optimal channel output states of a nonlinear channel, based on the Bayesian likelihood fitness function instead of a conventional Euclidean distance measure. In its searching procedure, all of the possible desired channel states are constructed with the elements of estimated channel output states. The desired state with the maximum Bayesian fitness is selected and placed at the center of a Radial Basis Function (RBF) equalizer to reconstruct transmitted symbols. In the simulations, binary signals are generated at random with Gaussian noise. The performance of the proposed method is compared with that of a hybrid genetic algorithm (GA merged with simulated annealing (SA): GASA), and the relatively high accuracy and fast searching speed are achieved.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제11권4호
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• pp.217-222
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• 2011

Genetic algorithms are one of the most important methods used to solve the Traveling Salesman Problem. Therefore, many researchers have tried to improve the Genetic Algorithm by using different methods and operations in order to find the optimal solution within reasonable time. This paper intends to find a new approach that adopts an improved genetic algorithm to solve the Traveling Salesman Problem, and compare with the well known heuristic method, namely, Kohonen Self-Organizing Map by using different data sets of symmetric TSP from TSPLIB. In order to improve the search process for the optimal solution, the proposed approach consists of three strategies: two separate tour segments sets, the improved crossover operator, and the improved mutation operator. The two separate tour segments sets are construction heuristic which produces tour of the first generation with low cost. The improved crossover operator finds the candidate fine tour segments in parents and preserves them for descendants. The mutation operator is an operator which can optimize a chromosome with mutation successfully by altering the mutation probability dynamically. The two improved operators can be used to avoid the premature convergence. Simulation experiments are executed to investigate the quality of the solution and convergence speed by using a representative set of test problems taken from TSPLIB. The results of a comparison between the new approach using the improved genetic algorithm and the Kohonen Self-Organizing Map show that the new approach yields better results for problems up to 200 cities.