• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.03a
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• pp.31-34
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• 1998

본 논문에서는 하이브리드 구조를 가지는 자기구성 퍼지제어기를 제안한다. 제안한 방법은 FARMA 제어기에 비해 다음과 같은 장점을 가진다. 하이브리드 구조를 자기구성 퍼지논리 제어기에 도입하므로써 예측출력값을 구할 때 까지의 입축력정보의 부재로 인한 나쁜 응답성능을 개선할 수 있다. 또한 이 방법은 Yager의 t-norm을 이용하여 계산상의 복잡성을 피하고 규칙들의 가중치를 구하기 위해 필요한 Dmax선정의 어려움을 해결한다.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.2
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• pp.21-34
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• 1998

[n this paper, we propose a hierarchical self-organizing fuzzy logic controller to improve the performance of the FARMA(Fuzzy auto-regressive moving average) SOC(Self-organizing fuzzy logic controller) when the system parameters change. The proposed controller contains the FARMA SC)C in the lower level and has a coordinator in the higher level, which evaluates convergence. and when it senses the degradation of system performance it compensates the control input by a look-up table. The proposed controller shows good perforniance over the FARMA SOC when the system parameters change. We executed some computer simulations on the regulation problem of an inlrerted pendulum system and compared the results with those of the FARMA SOC. As a result, it ha:; been shown that the proposed controller outperformed the FARMA SOC when the changes of the system parameters occurred.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.3
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• pp.21-33
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• 1997

In this paper, a method of self-organizing for fuzzy logic controller(FLC) through learning of the proper direction of coritrol is proposed. In case of designing a self-organizing FLC for unknown dynamic plants based on the gradient descent method, it is difficult to identify the desirable direction of the change of control inpul. in which the error would be decreased. To resolve this problem, we propose a method as fo1lows:at first, assign representative values for the direction of change of error with respect to control input to each partitioned region of the states, and then, learn the fuzzy control rules using the reinforced representative values through iterative trials. 'The proposed self-organizing FLC has simple structure and it is easy to design. The validity of the proposed method is proved by the computer simulation for an inverted pendulum system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.1
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• pp.165-177
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• 2000

A fuzzy controller need membership functions and the control rules depend on heuristic knowledge of expertises entirely. On account of, it is possible that a desired performance of a fuzzy controller can not be guaranteed or easily degraded under some circumstances such as a change of plant parameter which exporters do not considered. Therefore, in this paper we tried to increase the controller's efficiency by adjusting the control rules and the parameters of the membership functions by using a genetic algorithm. We also proposed the Self-Organizing Fuzzy Controller which uses the Fusion Method in order to minimize the number of control rules and to construct the intuitive controller. For validation of the proposed algorithm, we design the Autonomous Guided Vehicle Controller, then apply to variant condition.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.8
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• pp.92-98
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• 1995

The position control of flexible joint manipulator is investigated by applying the self-organizing fuzzy logic controller (SOC) proposed by Procyk and Mamdani. The SOC is a heuristic rule-based controller and a further extension of an ordinary fuzzy controller, which has a hierachy structrue which consists of an algorithm being identical to a fuzzy controller at the lower ollp and a learning algorithm accomodating the performance evalution and rule modification function at the upper ollp. This form of control can be used in those complex systems which have been too difficult to control or which in the past have had to rely on the experience of a human operator. Even though the significant dynamic coupling of the motors and links on the flexible joint manipulator, the performance of command-following is good by applying the proposed SOC.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.3
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• pp.267-272
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• 2012

This paper propose the implementation of robust fuzzy controller for controlling an active magnetic bearing (AMB) system with 6 degree of freedom (DOF). A basic model with 6 DOF rotor dynamics and electromagnetic force equations for conical magnetic bearings is proposed. The developed model has severe nonlinearity and uncertainty so that it is not easy to obtain the control objective. For solving this problem, we use the Takagi-Sugeno (T-S) fuzzy model which is suitable for designing fuzzy controller. The control object in the AMB system enables the rotor to rotate without any phsical contact by using magnetic force. In this paper, we analyze the nonlinearity of the active magnetic bearing system by using fuzzy control algorithm and desing the robust control algorithm for solving the parameter variation. Simulation results for AMB are demonstrated to visualize the feasibility of the proposed method.

• KSBB Journal
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• v.15 no.1
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• pp.14-21
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• 2000

In this study, algae cultivation using the photobioreactor has been applied to remove the nitrogen and phosphorus compounds in the wastewater of the livestock industry. The optimal ratio of nitrate and ortho-phosphate concentration was found for the enhancement of removal efficiency. To achieve the high density culture of algae, the photobioreactor consisted of optical fibers wes developed to get the sufficient light intensity. The light could be illuminated uniformly from light source to the entire reactor by the optical fibers. The structured kinetic model was proposed to describe the growth rate, consumption rate of nitrates and ortho-phosphates in algae culture. The self-organizing fuzzy logic controller incorporated with genetic algorithm was constructed to control the semi-continuous wastewater treatment system. The proposed fuzzy logic controller was applied to maintain the nitrated concentration at the given set-point with the control of wastewater feeding rate. The experimental results showed that the self-organizing fuzzy logic controller could keep the nitrate concentration and enhance algae growth.

• Journal of Internet Computing and Services
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• v.2 no.2
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• pp.105-116
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• 2001

According to increase of the factory-automation's(FA) in the field of production, the autonomous guided vehicle's(AGV) role is also increased, The study about an active and effective controller which can flexibly prepare for the changeable circumstance is in progressed. For this study. the research about ac1ion base system to evolve by itself is also being actively considered In this paper. we composed an ac1ive and effective AGV fuzzy controller to be able to do self-organization, For composing it. we tuned suboptimally membership function using genetic algorithm(GA) and improved the control efficiency by the self-correction and generating the control rules. self-organizing controlled(SOC) fuzzy controller proposed in this paper is capable of Self-organizing by using the characteristics of fuzzy controller and genetic algorithm. It intuitionally controls AGV and easily adapts to the circumstance.

• The Transactions of the Korean Institute of Power Electronics
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• v.2 no.4
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• pp.45-55
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• 1997

According to the increase of factory-automation in the field of production, the importance of autonomous guided vehicle's(AGV) role is also increased. The study about an active and effective controller which can flexibly prepare for the changeable circumstance is in progressed. For this study, the research about action base system to evolve by itself is also being actively considered. In this paper, we composed an active and effective AGV fuzzy controller to be able to do self-organization. For composing it, we tuned suboptimally membership function using genetic algorithm(GA) and improved the control efficiency by the self-correction and generating the control rules. Self-organizing controlled(S0C) fuzzy controller proposed in the paper is capable of self-organizing by using the characteristics of fuzzy controller and genetic algorithm. It intuitionally controls AGV and easily adapts to the circumstance.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.310-316
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• 1998

본 논문에서는 기존의 퍼지 제어규칙에비해 좋은 성능을 갖는 T-S(Takagi-Sugeno)퍼지 모델을 자기조직화 지도와 역전파 신경망을 이용하여 표현하고 제어기 구현을 위한 규칙의 자동 생성 방법을 제안한다. 제안된 방법은 신경망에 기초하여 T-S 퍼지 제어 규칙을 포현하므로써 학습 기능을 이용하여 지식 획득을 용이하게 하고, 입력 변수간의 퍼지 관계에 기반 하여 추론이 이루어지므로 각 퍼지 변수에 대한 소속 함수의 정의 과정이 불필요하게 된다. 또한 제어기로 구현되었을 때 규칙의 수나 퍼지화 및 비퍼지화 등이 구성된 추론망을 통하여 자동으로 수행될 수 있다. 때문에 퍼지 시스템의 구현이 쉽게 이루어 질 수 있게 한다. 제안된 방법을 자동차 궤도 안정화 모의 실험에 적용해 봄으로써 추론망이 규칙을 생성하여 타당한 추론을 하게 됨을 확인한다.