• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.11
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• pp.53-67
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• 1998

This paper suggests a method designing the TSK fuzzy controller based on the TSK fuzzy model, which guarantees the stability of the closed loop system and makes the response of the closed loop system to be a desired one. This paper deals with the general type of TSK fuzzy model of which consequents are affine equations having a constant term. The TSK fuzzy controller suggested in this paper is designed by using the pole placement which developed for the linear systems and makes the closed loop system have the same behavior as a desired linear system. A reference input can be introduced to the suggested TSK fuzzy controller and an integral action also can be introduced. Simulation results reveal that the suggested methods are practically feasible. This paper deals with both the continuous systems and the discrete systems.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.2
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• pp.325-333
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• 2016

This paper proposes controller design algorithms for a ceramic soldering iron temperature control system, and reports their effectiveness in a control experiment. Because the responses of the ceramic soldering iron temperature to the control input are non-linear and very slow, precise modeling and controller design is difficult. In this study, the temperature characteristics of a ceramic soldering iron are represented by TSK fuzzy models consisting of TSK fuzzy rules. In the fuzzy rules, the premise variable is the control input and the consequences are the transfer functions. The transfer functions in the fuzzy model were obtained from the step input responses. As the responses of the ceramic soldering iron temperature are very slow, it is difficult to obtain the complete step input responses. This paper proposes a genetic algorithm to obtain the transfer functions from an incomplete step input responses, and showed its effectiveness in examples. This paper also reports a fuzzy controller design method from the TSK fuzzy model and examples. The proposed methods were applied to the temperature control experiments of ceramic iron. The TSK fuzzy model consisted of 7 TSK fuzzy rules, and the consequences were PI controllers. The experimental results of the proposed fuzzy PI controller were superior to the linear controller and were as good as in previous studies using a fuzzy PID controller.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.3
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• pp.676-683
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• 2005

In this paper, we proposed a method that optimal values of fuzzy control rule base and quantization of membership function are searched by genetic algorithm. Proposed method searched the optimal values of membership function and control rules using genetic algorithm by off-line. Then fuzzy controller operates using these values by on-line. Proposed fuzzy control system is optimized the control rule base and membership function by genetic algorithm without expert's knowledge. We investigated proposed method through simulation and experiment using DC motor and one link manipulator, and confirmed the following usefulness.

• 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.

• The Transactions of the Korean Institute of Power Electronics
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• v.15 no.5
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• pp.343-351
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• 2010

This paper proposes a new fuzzy speed controller based on the Takagi-Sugeno fuzzy method to achieve a robust speed control of a permanent magnet synchronous motor (PMSM). The proposed controller requires the information of the load torque, so the second-order load torque observer is used to estimate it. The LMI condition is derived for the existence of the proposed fuzzy speed controller, and the gains of the controller are provided. It is proven that the augmented control system including the fuzzy speed controller and the load torque observer is exponentially stable. To evaluate the performance of the proposed fuzzy speed controller, the simulation and experimental results are presented under motor parameter variations. Finally, it is clearly verified that the proposed control method can accurately control the speed of a permanent magnet synchronous motor.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.3
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• pp.241-245
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• 2001

The existing fuzzy traffic controllers construct the rule-base based on the intuitive knowledge and experience or the standard rule-base, but the rule-base constructed by the above methods has difficulty in representing exactly and detailedly the control knowledge of the export and the operator. Therefore, in this paper, we propose a method that can improve the performance of the fuzzy traffic control by designing the fuzzy traffic controller which represents the control knowledge more exactly. The proposed method so modifies the position and shape of the fuzzy membership function based on the input-output data clustering that the fuzzy traffic controller can represent the control knowledge more exactly. Our method use the rough control knowledge based on intuitive knowledge and experience as the evaluation function for clustering the input-output data. The fuzzy traffic controller designed by the our method could represent the control knowledge of the expert and the operator more exactly, and it outperformed the existing controller in terms of the number of passed vehicles and the wasted green-time.

• Proceedings of the KIEE Conference
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• 2006.04b
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• pp.358-361
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• 2006

태양전지는 일사량에 따라 그 출력특성이 변하기 때문에 전지로부터 최대출력을 얻기 위해서는 컨버터에 의한 최대 전력점 추종제어가 필요하다. 본 논문에서는 태양광 발전시스템의 최대전력추종을 위해 퍼지이론을 도입한 퍼지제어기를 설계하였다. 퍼지제어기의 디지털 설계를 위해 태양광 발전시스템을 각 부분을 구성하고, FPGA를 사용하여 제어기를 구현하였다. 또한 실험을 통해 FPGA의 퍼지제어기로서의 구현가능성을 발견하고 그 타당성을 입증하고자 한다.

• Proceedings of the KIPE Conference
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• 2006.06a
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• pp.210-212
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• 2006

태양전지는 일사량에 따라 그 출력특성이 변화하기 때문에 태양전지로 부터 최대출력을 얻기 위해서는 컨버터에 의한 최대 전력점 추종제어가 필요하다. 본 연구에서는 태양광 발전 시스템의 최대전력추종을 위해 퍼지 이론을 도입한 퍼지제어기를 설계하였다. 그리고 퍼지제어기의 디지털 설계를 위해 태양광 발전시스템의 각 부분을 구성하고, 마이크로프로세서와 FPGA의 두가지 방식으로 제어기를 구현하였다. 또한 구현된 두 가지 방식의 퍼지제어기에 대해 실험을 통하여 비교분석 하였다.

• Proceedings of the KAIS Fall Conference
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• 2006.05a
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• pp.271-275
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• 2006

본 논문에서는 태양광 발전시스템의 최대전력추종을 위해 퍼지 이론을 도입한 퍼지제어기를 설계하였다. 퍼지제어기의 디지털 설계를 위해 태양광 발전시스템의 각 부분을 구성하고, FPGA를 사용하여 제어기를 구현하였다. 구현된 제어기는 일사량의 변화에도 안정적으로 동작하며, 출력전압의 리플이 작은 결과를 보였다. 또한 FPGA의 퍼지제어기로서의 구현가능성을 발견하고 그 타당성을 입증하였다.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.8 no.1
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• pp.46-52
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• 1994

In this paper, we implemented the variable speed controller of an induction motor by the Fuzzy control algorithms, which recently is invoking the remarkable interest. As the fuzzy controller is designed on the base of expert's knowlede and experience, it is difficult to expect the perfect control performance of fuzzy controller. Therefore, the adjustment techniques for optimization of scale factors were presented to design the robust fuzzy controller comparing with conventional PI control the usefullness of proposed fuzzy controller was showed by the experimental results.