• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.11a
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• pp.363-366
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• 2000

본 논문에서는 브러쉬없는 직류전동기의 위치제어를 위한 직접적응 퍼지가변구조제어기를 설계한다. 가변구조제어는 시스템의 파라메터 변화나 외란에 둔감한 특성을 갖는 반면 떨림현상의 문제점을 가지고 있다. 떨림현상의 진폭은 시스템의 불확실정보를 최악의 상태로 가정한 후 결정되므로, 기존의 가변구조제어에서는 그 크기가 너무 크다. 또한 이런 불확실한 요소들의 최대값은 찾아내기도 어렵다. 본 논문에서는 불확실한 요소의 최대값을 최적으로 추정하기 위하여 퍼지 추론 기법을 사용한다. 아울러 소속함수의 원소들을 직접적응 기법에 의하여 자동 조정할 수 있는 기법을 추가한다. 이를 통하여 우수한 제어 성능을 얻을 수 있음을 확인한다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.11a
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• pp.489-492
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• 2000

브러쉬없는 직류전동기의 위치제어를 위한 퍼지가변구조제어기를 설계한다. 특히 본 논문에서는 기존의 퍼지제어 기법에서 얻을수 있는 특징으로부터 하나의 전건부 변수만을 가지는 간단한 퍼지논리제어기의 설계를 기술한다. 가변구조제어는 시스템의 파라메터 변화나 외란에 둔감한 특성을 갖는다. 하지만 리칭페이스에서는 문제가 된다. 이를 개선하기 위하여 본 논문에서는 지수항을 추가한 비선형 슬아이딩면을 구성한다. 그리고 나서 비선형적 슬라이딩면과 슬라이딩면의 변화율을 입력으로하는 퍼지 제어기를 설계한다. 이러한 2-입력 퍼지가변구조제어기의 제어 규칙표로부터 슬라이딩면 하나만을 입력으로 가지는 단일입력 퍼지 가변구조 제어기를 설계한다. 이들 제어기의 성능을 입증하기 위하여 시뮬레이션과 실험을 수행한다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.4
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• pp.275-279
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• 2011

In this paper, an observer-based sampled-data controller of linear system is proposed for the wave energy converter. Based on the sampled-data observer, the controller is design. In the closed-loop system with controller, it obtains the norm inequality between the continuous-time state variable and the discrete-time one. Using the norm inequality, sufficient condition is derived for the asymptotic stability of the closed-loop system and formulated in terms of linear matrix inequality. Finally, the wave energy converter simulation is provided to verify the effectiveness of the proposed technique.

• Journal of the Korean Society of Safety
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• v.14 no.3
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• pp.54-62
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• 1999

This paper presents a study on the safety assessment of human body for electromagnetic field at unbalanced power system. The 3-phase load flow algorithm uses Newton-Raphson method based on Taylor series expansion of power flow equations in rectangular coordinates. The use of such a method can result in a solution with good convergence characteristics. In the safety assessment of human body, the approach based on fuzzy linguistic variable is employed to overcome the shortcomings resulting from a crisp set concept. The suggested scheme is applied to a 24bus system to validate the usefulness. The results for an unbalanced power system are compared with the results for a balanced power system.

• Journal of Korean Institute of Industrial Engineers
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• v.28 no.1
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• pp.25-35
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• 2002

This paper presents a heuristic algorithm that a mobile robot avoids obstacles using optical flow. Using optical flow, the mobile robot can easily avoid static obstacles without a prior position information as well as moving obstacles with unknown trajectories. The mobile robot in this paper is able to recognize the locations or routes of obstacles, which can be detected by obtaining 2-dimensional optical flow information from a CCD camera. It predicts the possibilities of crash with obstacles based on the comparison between planned routes and the obstacle routes. Then it modifies its driving route if necessary. Driving acceleration and angular velocity of mobile robot are applied as controlling variables of avoidance. The corresponding simulation test is performed to verify the effectiveness of these factors. The results of simulation show that the mobile robot can reach the goal with avoiding obstacles which have variable routes and speed.

• Journal of Distribution Science
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• v.11 no.6
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• pp.13-19
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• 2013

Purpose - This study aims to predict the audit reports of listed companies on the Tehran Stock Exchange by using meta-heuristic algorithms. Research design, data, methodology - This applied research aims to predict auditors reports' using meta-heuristic methods (i.e., neural networks, the ANFIS, and a genetic algorithm). The sample includes all firms listed on the Tehran Stock Exchange. The research covers the seven years between 2005 and 2011. Results - The results show that the ANFIS model using fuzzy clustering and a least-squares back propagation algorithm has the best performance among the tested models, with an error rate of 4% for incorrect predictions and 96% for correct predictions. Conclusion - A decision tree was used with ten independent variables and one dependent variable the less important variables were removed, leaving only those variables with the greatest effect on auditor opinion (i.e., net-profit-to-sales ratio, current ratio, quick ratio, inventory turnover, collection period, and debt coverage ratio).

• Journal of the Korea Safety Management & Science
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• v.3 no.3
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• pp.1-9
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• 2001

To keep an enterprise's competitiveness on the condition of the automatic manufacturing system such as FA, FMS and CIM, all the maintenance problems should be considered seriously In not only in production and maintenance but also in related industrial safety. As we analyze in the surveys the maintenance management of domestic enterprises and the causes of Industrial accident, there will be necessity of drawing up countermeasures for preventing industrial accidents and for ensuring expertise maintenance technologies. Based on these analyses, the safety information system, maintenance management information system, and the machinery condition diagnosis technique are studied by using of the knowledge-based system under the real-time computer-operating environment and using fuzzy linguistic variable. This computer system based knowledge-based diagnosis can easily provide not only the knowledge of expert system about deterioration phenomenon of industrial robots, but also the knowledge of relating safety and facility all the time. Therefore, it is expected to improve the efficiency of business processes in the production and safety when we use this system.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.1 no.1
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• pp.29-34
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• 2001

This paper is devoted to investigating direct adaptive neural control of nonlinear systems with uncertain or unknown dynamic models. In the direct adaptive neural networks control area, theoretical issues of the existing backpropagation-based adaptive neural networks control schemes. The major contribution is proposing the variable index control approach, which is of great significance in the control field, and applying it to derive new stable robust adaptive neural network control schemes. This new schemes possess inherent robustness to system model uncertainty, which is not required to satisfy any matching condition. To demonstrate the feasibility of the proposed leaning algorithms and direct adaptive neural networks control schemes, intensive computer simulations were conducted based on the flexible joint robot systems and functions.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.261-263
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• 2009

본 연구에서는 복잡한 비선형 모델링 방법인 RBF 뉴럴 네트워크(Radial Basis Function Neural Network)와 PNN(Polynomial Neural Network)을 접목한 새로운 형태의 Radial Basis Function Polynomial Neural Network(RPNN)를 제안한다. RBF 뉴럴 네트워크는 빠른 학습 시간, 일반화 그리고 단순화의 특징으로 비선형 시스템 모델링 등에 적용되고 있으며, PNN은 생성된 노드들 중에서 우수한 결과값을 가진 노드들을 선택함으로써 모델의 근사화 및 일반화에 탁월한 효과를 가진 비선형 모델링 방법이다. 제안된 RPNN모델의 기본적인 구조는 PNN의 형태를 이루고 있으며, 각각의 노드는 RBF 뉴럴 네트워크로 구성하였다. 사용된 RBF 뉴럴 네트워크에서의 커널 함수로는 FCM 클러스터링을 사용하였으며, 각 노드의 후반부는 다항식 구조로 표현하였다. 또한 각 노드의 후반부 파라미터들은 최소자승법을 이용하여 최적화 하였다. 제안한 모델의 적용 및 유용성을 비교 평가하기 위하여 비선형 데이터를 이용하여 그 우수성을 보인다.

• Journal of Power Electronics
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• v.9 no.2
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• pp.207-214
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• 2009

This paper presents a modem approach for speed control of a PMSM using the Particle Swarm Optimization (PSO) algorithm to optimize the parameters of the PI-Controller. The overall system simulated under various operating conditions and an experimental setup is prepared. The use of PSO as an optimization algorithm makes the drive robust, with faster dynamic response, higher accuracy and insensitive to load variation. Comparison between different controllers is achieved, using a PI controller which is tuned by two methods, firstly manually and secondly using the PSO technique. The system is tested under variable operating conditions. Implementation of the experimental setup is done. The simulation results show good dynamic response with fast recovery time and good agreement with experimental controller.