• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 D
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• pp.2633-2635
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• 2000

In this paper, a new DNA coding method, namely modified DNA coding method based on the biological DNA and the evolution mechanism of genetic algorithm. In order to evaluate the propose algorithms, for an example, they are applied to the fuzzy control of parallel double inverted pendulum system. Simulation result show the method is effective in finding the fuzzy control rules and is more excellent than conventional methods in control the system.

• Industrial Engineering and Management Systems
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• 제15권4호
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• pp.354-363
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• 2016

Due to uncertain environment, various parameters such as price, queuing length, warranty, and so on influence on inventory models. In this paper, an inventory-queuing-pricing problem with continuous review inventory control policy and batch arrival queuing approach, is presented. To best of our knowledge, (I) demand function is stochastic and price dependent; (II) due to the uncertainty in real-world situations, a fuzzy programming approach is applied. Therefore, the presented model with goal of maximizing total profit of system analyzes the price and order quantity decision variables. Since the proposed model belongs to NP-hard problems, Pareto-based approaches based on non-dominated ranking and sorting genetic algorithm are proposed and justified to solve the model. Several numerical illustrations are generated to demonstrate the model validity and algorithms performance. The results showed the applicability and robustness of the proposed soft-computing-based approaches to analyze the problem.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 D
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• pp.2458-2460
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• 2000

The goal of crane control system is transporting heavy objects to a target position as fast as possible without rope oscillation. This paper presents a GA-based fuzzy logic controller for crane system. GA is going to decide membership functions, instead of an expert. In this paper, The centers and widths of the membership function of the fuzzy sets defined over the input space, the orders and parameters of subsystems in the consequence parts are adjusted by a genetic algorithm. The effectiveness of the proposed method is verified by simulation.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 D
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• pp.2473-2475
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• 2000

In this paper, we design a GA-fuzzy controller for position control and anti-swing at the destination point. Applied genetic algorithm is used to complement the demerit such as the difficulty of the component selection of fuzzy controller, namely, scaling factor, membership function and control rules. Lagrange equation is used to represent the motion equation of trolley and load in order to obtain mathematical modelling.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 D
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• pp.2837-2839
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• 2000

We design a stable controller for a mobile robot with variable gains and reference velocity in order to apply the proper gains and reference velocity, which are generated with fuzzy logic in on-line. The stability is guranteed by the Lyapunov theory. The fuzzy logic rules is found in off-line with GA strategy which drives each object function to be the least. The proposed controller is applied smooth path tracking due to the local path planing. Simulation results show robust performances under a different initial conditions.

• Journal of information and communication convergence engineering
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• 제3권1호
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• pp.43-48
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• 2005

In this paper, the adaptive fuzzy logic controller(AFLC) is proposed, which uses real-coding genetic algorithm showing a good performance on convergence velocity and diversity of population among evolutionary computations. The effectiveness of the proposed AFLC was demonstrated by computer simulation for speed control system of AC servo motor. As a result of simulation for the AC servo motor, it is shown the proposed AFLC has the better performance on overshoot, settling time and rising time than the PI controller which is used when tuning AFLC.

• 한국지능시스템학회논문지
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• 제7권4호
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• pp.82-92
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• 1997

본 논문에서는, 퍼지 측도와 퍼지 적분을 이용한 상호 작용 시스템의 모델 및 이의 식별볍을 제시한다. 모델 식별은 다음과 같은 세 단계를 거쳐 이루어 지는데, 그 첫번째는 모델의 구조 식별이고 두번째는 식별된 구조를 갖는 모델의 파라메터 식별이다. 그리고 마지막으로는 식별된 구조와 파라메터를 갖는 모델의 최적성을 판단하여, 최적의 모델을 선정하게 된다. 본 논문에서는 최적 모델의 식별을 위하여 유전자 알고리즘 및 통계적 모델 선택 기준을 이용하여, 최적 모델들의 후보군으로부터 최적모델을 선정하는 알고리즘을 제시한다. 본 논문에서 제시된 모델 및 이의 식별법의 타당성을 보이기 위하여, 주관적 평가 데이타 및 시계열 데이타에 적용하여 그 결과를 나타내었으며, 또한 기존의 다른 모델들로부터 얻어진 결과와 비교 검토하였다.

• 전기학회논문지
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• 제59권2호
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• pp.436-444
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• 2010

In this study, we introduce and discuss a concept of a granular-oriented radial basis function neural networks (GRBF NNs). In contrast to the typical architectures encountered in radial basis function neural networks(RBF NNs), our main objective is to develop a design strategy of GRBF NNs as follows : (a) The architecture of the network is fully reflective of the structure encountered in the training data which are granulated with the aid of clustering techniques. More specifically, the output space is granulated with use of K-Means clustering while the information granules in the multidimensional input space are formed by using a so-called context-based Fuzzy C-Means which takes into account the structure being already formed in the output space, (b) The innovative development facet of the network involves a dynamic reduction of dimensionality of the input space in which the information granules are formed in the subspace of the overall input space which is formed by selecting a suitable subset of input variables so that the this subspace retains the structure of the entire space. As this search is of combinatorial character, we use the technique of genetic optimization to determine the optimal input subspaces. A series of numeric studies exploiting some nonlinear process data and a dataset coming from the machine learning repository provide a detailed insight into the nature of the algorithm and its parameters as well as offer some comparative analysis.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제5권3호
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• pp.206-215
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• 2005

In this paper, we propose a new design method of Genetic Algorithm Processor(GAP) and Evolvable Hardware(EHW). All sorts of creature evolve its structure or shape in order to adapt itself to environments. Evolutionary Computation based on the process of natural selection not only searches the quasi-optimal solution through the evolution process, but also changes the structure to get best results. On the other hand, Genetic Algorithm(GA) is good fur finding solutions of complex optimization problems. However, it has a major drawback, which is its slow execution speed when is implemented in software of a conventional computer. Parallel processing has been one approach to overcome the speed problem of GA. In a point of view of GA, long bit string length caused the system of GA to spend much time that clear up the problem. Evolvable Hardware refers to the automation of electronic circuit design through artificial evolution, and is currently increased with the interested topic in a research domain and an engineering methodology. The studies of EHW generally use the XC6200 of Xilinx. The structure of XC6200 can configure with gate unit. Each unit has connected up, down, right and left cell. But the products can't use because had sterilized. So this paper uses Vertex-E (XCV2000E). The cell of FPGA is made up of Configuration Logic Block (CLB) and can't reconfigure with gate unit. This paper uses Vertex-E is composed of the component as cell of XC6200 cell in VertexE

• 한국지능시스템학회논문지
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• 제17권5호
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• pp.640-647
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• 2007

본 논문은 유전알고리즘을 기초로 한 휴머노이드 로봇의 관절 제어에 관한 논문이다. 휴머노이드 로봇은 지면에 고정된 시스템이 아니기 때문에 기본적으로 불안정성을 내포하고 있다. 게다가 각 관절의 비선형성은 로봇의 안정성에 악영향을 미친다. 이에 만약 둘 중 하나라도 안정하지 못하면 로봇은 보행 중에 넘어지게 될 것이므로, 휴머노이드 로봇의 안정성을 확보하기 위해서는 이 두 가지가 모두 고려되어야 할 것이다. 이에 본 논문에서는 보행 안정성을 확보하기 위해 이 두 가지 문제 중에 로봇의 비선형성을 제거하면서 로봇이 주어진 궤적을 잘 추종하여 제어할 수 있는 제어기를 제안하였다. 이 제어기는 퍼지-슬라이딩 모드 제어기를 기본으로 하고 있으면서 모션 제어기가 첨가되어 있다. 그리고 이때 이러한 제어 이득값을 유전알고리즘을 통해 추종함으로써 보다 정밀한 제어가 가능하도록 하여 휴머노이드 로봇이 보다 안정적으로 보행할 수 있도록 하였다. 이 모든 과정은 시뮬레이션과 실험을 통해 검증하였다.