• Transactions on Control, Automation and Systems Engineering
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• 제4권4호
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• pp.330-340
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• 2002

In this Paper. a non-linear approach to a design of model reference adaptive control is presented. The approach is demonstrated by a case study of a simple single-pole and no zero, linear, discrete-time plant. The essence of the idea is to generate a full non-linear model of the plant dynamics and the parameter adaptation dynamics as a gradient descent algorithm with respect to a Riemannian metric. It is shown how a Riemannian metric can be chosen so that the modelled plant dynamics do in fact match the true plant dynamics. The performance of the proposed scheme is compared to a traditional model reference adaptive control scheme using the classical sensitivity derivatives (Euclidean gradients) for the descent algorithm.

• Transactions on Control, Automation and Systems Engineering
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• 제3권1호
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• pp.58-65
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• 2001

This paper proposes a self tuning fuzzy inference method by the genetic algorithm in the fuzzy-sliding mode control for a robot. Using this method, the number of inference rules and the shape of membership functions are optimized without an expert in robotics. The fuzzy outputs of the consequent part are updated by the gradient descent method. And, it is guaranteed that he selected solution become the global optimal solution by optimizing the Akaikes information criterion expressing the quality of the inference rules. The trajectory tracking simulation and experiment of the polishing robot show that the optimal fuzzy inference rules are automatically selected by the genetic algorithm and the proposed fuzzy-sliding mode controller provides reliable tracking performance during the polishing process.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2002년도 추계학술대회 및 정기총회
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• pp.113-117
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• 2002

PID controllers, which have been widely used in industry, have a simple structure and robustness to modeling error. But it is difficult to have uniformly good control performance in system parameters variation or different velocity command. In this paper, we propose a nonlinear adaptive PR controller based on an Immune feedback mechanism and a gradient descent teaming. This algorithm has a simple structure and robustness to system parameters variation. To verify performances of the proposed nonlinear adaptive PID controller, the speed control of nonlinear DC motor Is peformed. The simulation results show that the proposed control systems are effective in tracking a command velocity under system parameters variation

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 학술회의 논문집 정보 및 제어부문 B
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• pp.421-424
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• 2003

This paper proposes the generalized predictive control(GPC) method of chaotic systems using a self-recurrent wavelet neural network(SRWNN). The reposed SRWNN, a modified model of a wavelet neural network(WNN), has the attractive ability such as dynamic attractor, information storage for later use. Unlike a WNN, since the SRWNN has the mother wavelet layer which is composed of self-feedback neurons, mother wavelet nodes of the SRWNN can store the past information of the network. Thus the SRWNN can be used as a good tool for predicting the dynamic property of nonlinear dynamic systems. In our method, the gradient-descent(GD) method is used to train the SRWNN structure. Finally, the effectiveness and feasibility of the SRWNN based GPC is demonstrated with applications to a chaotic system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권4호
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• pp.1760-1778
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• 2018

For image segmentation with intensity inhomogeneity, many region-based level set methods have been proposed. Some of them however can't get the relatively ideal segmentation results under the severe intensity inhomogeneity and weak edges, and without use of the image gradient information. To improve that, we propose a new level set method combined with local direction gradient in this paper. Firstly, based on two assumptions on intensity inhomogeneity to images, the relationships between segmentation objects and image gradients to local minimum and maximum around a pixel are presented, from which a new pixel classification method based on weight of Euclidian distance is introduced. Secondly, to implement the model, variational level set method combined with image spatial neighborhood information is used, which enhances the anti-noise capacity of the proposed gradient information based model. Thirdly, a new diffusion process with an edge indicator function is incorporated into the level set function to classify the pixels in homogeneous regions of the same segmentation object, and also to make the proposed method more insensitive to initial contours and stable numerical implementation. To verify our proposed method, different testing images including synthetic images, magnetic resonance imaging (MRI) and real-world images are introduced. The image segmentation results demonstrate that our method can deal with the relatively severe intensity inhomogeneity and obtain the comparatively ideal segmentation results efficiently.

• Composites Research
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• 제13권2호
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• pp.40-50
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• 2000

종횡비가 다른 적층복합재료에 경사형 구조를 도입하고, 이것이 일방향으로의 하중을 받을 때의 좌굴특성을 최대화하기 위해서 복합재료의 각 층에서의 섬유부피분율과 두께를 변수로 sequential linear programming method를 이용하여 최적화 하였다. 이로부터 좌굴특성을 최대화 할 수 있는 최적구조를 제안하였다. 적층복합재료는 종횡비의 영향이 커서 종횡비가 1보다 작은 경우는 최외각층의 섬유부피분율을 최대화하는 방향으로 최적화가 이루어졌으나 종횡비가 2인 경우는 각층에서의 섬유부피분율과 두께비가 어느 정도 균형을 이루는 형태로 최적화가 이루어 졌다. 경사형 구조는 전통적인 균일구조의 복합재료에 비해서 섬유부피와 복합재료의 무게 절감에 큰 효과를 가지는 것으로 확인되었다.

• 한국전산유체공학회지
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• 제18권1호
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• pp.43-48
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• 2013

The feasibility of a unique greenhouse, named as Gradient Biome, is now being examined extensively in the University of Tokyo. It is a large chamber (length:200m, width:50m, height:40m) in which the weather, such as temperature and humidity, of the tropical zone through to that of the frigid zone on the earth is reproduced with continuous gradient. In the Gradient Biome, ecosystems (mainly plants) corresponding to each weather are introduced and the possible responses of this ecosystems to the expected global warming are to be observed. Since one of the expected responses is the shift of the ecosystem(s) toward the region of suitable environment, there should be no artificial obstacles, which can prevent the shift, inside the Biome. This requirement is not so easy to be satisfied since the environment tends to be homogeneous. This paper presents the results of the numerical studies conducted to find the ways of how the temperature and humidity in the Gradient Biome could be reproduced. One of the contributed solvers of OpenFOAM, which is an open source physics simulation code, was modified and used for the numerical simulations.

• 한국지능시스템학회논문지
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• 제13권1호
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• pp.24-30
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• 2003

본 논문에서는 혼돈 시스템을 제어하기 위해 웨이블릿 신경 회로망을 예측기로 사용하여 일반형 예측 제어기를 설계하는 방법을 제안한다. 본 논문의 방법에서는 웨이블릿 신경 회로망의 각 파라미터에 대한 학습은 예측 오차를 이용한 경사 하강법에 의해 수행되며, 제어 신호는 웨이블릿 신경 회로망의 출력과 기준 신호 사이의 제어 오차를 최소화함으로써 생성된다. 한편, 모의 실험을 통해 본 논문에서 제안한 제어기를 각각 연속 시간 혼돈 시스템인 Doffing 시스템과 이산 시간 혼돈 시스템인 Henon 시스템에 적용하여 제어기의 효율성을 확인하고 아울러 신경 회로망을 이용한 예측 제어의 결과와 비교함으로써 제어기의 우수성을 검증한다

• Applied Science and Convergence Technology
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• 제24권5호
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• pp.184-189
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• 2015

We report a simple way to enhance the size gradient of an imprinted nanopattern through oxygen plasma etching under a nonuniform magnetic field. A sample substrate was placed next to a magnet, and then a nonuniform magnetic field condition was formed around the sample. Using oxygen plasma etching, a line pattern having an initial width of 273 nm was gradually modified from 248 nm at one end to 182 nm at the other end. Controlling the arrangement of the magnet and sample, we could induce a triangular shape size gradient. We verified that the gradually modified nanopatterns we produced are applicable to continual optical property control, showing a possibility to be utilized for optical components such as gratings and polarizers.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제15권4호
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• pp.251-259
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• 2015

In this paper, a ship detection method is proposed; this method uses edge-based segmentation and histogram of oriented gradient (HOG) with the ship size ratio. The proposed method can prevent a marine collision accident by detecting ships at close range. Furthermore, unlike radar, the method can detect ships that have small size and absorb radio waves because it involves the use of a vision-based system. This system performs three operations. First, the foreground is separated from the background and candidates are detected using Sobel edge detection and morphological operations in the edge-based segmentation part. Second, features are extracted by employing HOG descriptors with the ship size ratio from the detected candidate. Finally, a support vector machine (SVM) verifies whether the candidates are ships. The performance of these methods is demonstrated by comparing their results with the results of other segmentation methods using eight-fold cross validation for the experimental results.