• 산업기술연구
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• 제15권
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• pp.195-202
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• 1995

In this paper, we analyze the effects of scaling factors on the performance of a fuzzy controller. The quantitative relation between input and output variables of a fuzzy controller is obtained by using a quasi-linear fuzzy model. And an approximate transfer function of a fuzzy controller is derived from the comparison of fuzzy controller with the conventional PID controller. Then we analyze the effects of scaling factor using this approximate transfer function and root locus method.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제1권1호
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• pp.1-5
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• 2001

In this paper, we propose a fuzzy traffic controller that is able to cope with traffic congestion appropriately. In order to consider such situation as loss of green time caused by spillback of upper crossroad, it imports a degree of traffic congestion of upper roads which vehicles on a crossroad are to proceed to. We constructed the equal-partitioned fuzzy traffic controller that uses the membership functions of the same size and shape, and modified the size and shape, and modified the size and shape of its membership functions by the membership function modification algorithm. In experiment, we compared and analyzed the fixed signal controller, the fuzzy traffic controller with the membership of the same size and shape, and the modified fuzzy traffic controller by using the delay time, the proportion of entered vehicles to occurred vehicles and the proportion of passed vehicles to entered vehicles. As a result of experiment, the modified fuzzy controller showed more enhanced performance than others.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 하계학술대회 논문집 D
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• pp.2120-2122
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• 2002

There are several types of control systems that use fuzzy logic controller as a essential system component. The majority of research work on fuzzy PID controller focuses on the conventional two-input PI or PD type controller. However, fuzzy PID controller design is a complex task due to the involvement of a large number of parameters in defining the fuzzy rule base. In this paper we combined conventional PI type and PD type fuzzy controller and set the initial parameters of this controller from the conventional PID controller gains obtained by Ziegler-Nichols tuning or other coarse tuning methods. After that, by replacing some of these parameters with sing1e neurons and making them to be adjusted by back-propagation learning algorithm we designed a neuro-fuzzy controller which showed good performance characteristics in both computer simulation and actual application.

• 한국지능시스템학회논문지
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• 제13권3호
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• pp.287-292
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• 2003

로봇의 기능이 다양해지며 복잡해지고 있다. 주위의 환경을 감지하는 센서로는 거리정보 뿐만 아니라 영상 정보, 음성 정보까지 이용하고 있다. 본 논문에서는 다양한 입력정보를 가진 로봇을 제어하기 위한 알고리즘으로 2-layer fuzzy control을 제안한다. 장애물 회피의 경우에 다수의 거리 센서를 이용하는데 이것을 앞쪽, 왼쪽, 오른쪽으로 분류하여 3개의 sub-controller를 가지고 퍼지 추론을 한 다음, 2단계에서는 이 3개의 sub-controller의 출력으로 조합된 퍼지 추론을 하여 통합적인 제어를 한다. 본문에서는 2-layer fuzzy controller와 비슷한 구조를 갖는 hierarchical fuzzy controller와 비교를 하였으며 robot following에도 적용하여 각각에 대한 시뮬레이션과 실험을 통해 성능을 확인한다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 학술대회 논문집 정보 및 제어부문
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• pp.352-354
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• 2004

In this paper, a parallel fuzzy controller for one degree of freedom magnetic levitation is designed and its performance is compared with the performance of a PID controller. Input, output scaling factor of fuzzy controller and gain of PID controller were tuned using the GA algorithm. The designed controllers are validated by numerical simulations. So it's shown that parallel fuzzy controller can give the better performance for the plant than PID controller.

• Journal of Electrical Engineering and Technology
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• 제3권3호
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• pp.337-345
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• 2008

This paper presents a new approach to the design of a rough fuzzy controller for the control loop of the SVC (static VAR system) in a two area power system for stability enhancement with particular emphasis on providing effective damping for oscillatory instabilities. The performances of the rough fuzzy and the conventional fuzzy controller are compared with that of the conventional PI controller for a variety of transient disturbances, highlighting the effectiveness of the rough fuzzy controller in damping the inter-area oscillations. The effect of the rough fuzzy controller in improving the CCT (critical clearing time) of the two area system is elaborated in this paper as well.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2001년도 춘계학술대회 학술발표 논문집
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• pp.144-147
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• 2001

This paper presents adaptive fuzzy controller which is uncertainty or unknown variation in different parameters with nonlinear system of helicopter. The proposed adaptive fuzzy controller applied TSK(Takagi-Sugeno-Kang) fuzzy system which is not only low number of fuzzy rule, and a linear input-output equation with a constant term, but also can represent a large class of nonlinear system with good accuracy. The adaptive law was designed by using Lyapunov stability theory. The adaptive fuzzy controller is a model reference adaptive controller which can adjust the parameter $\theta$ so that the plant output tracks the reference model output. First of all, system of helicopter was considered as stopping state, and design of controller was simulated from dynamics equation with stopping state. Results show that it is controlled more successfully with a model reference adaptive controller than with a non-adaptive fuzzy controller when there is a modelling error between system and model or a continuous added noise in such unstable system.

• 대한전기학회논문지
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• 제43권3호
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• pp.468-477
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• 1994

Existing fuzzy control methods do not perform well when applied to systems containing nonlinearities arising from unkonwn deadzones. In particular, we show that a conventional fuzzy logic controller applied to a system with a deadzone suffers from poor transient performance and a large steady-syate error. In this paper, we propose a novel two-layered fuzzy logic controller for controlling systems with deadzones. The two-layered control structure consists of a fuzzy logic-based precompensator followed by a conventional fuzzy logic controller. Our proposed controller exhibits superior transient and steady-state performance compared to conventional fuzzy controllers. In addition, the controller is robust to variations in deadzone nonlinearities. We illustrate the effectiveness of our scheme using computer simulation examples.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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• pp.459-464
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• 1998

In this paper, we propose a stable fuzzy logic controller architecture for inverted pendulum,. In the design procedure, we represent the fuzzy system as a Takagi-Sugeno fuzzy model and construct a global fuzzy logic controller by considering each local state feedback controller and a supervisory controller, Unlike usual parallel distributed controller, one can design a global stable fuzzy controller without finding a common Lyapunov function by the proposed method. A simulation is performed to control the inverted pendulum to show the effectiveness and feasibility of the proposed fuzzy controller.

• 전기학회논문지
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• 제60권2호
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• pp.330-337
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• 2011

This paper presents a new fuzzy speed controller based on a fuzzy angular acceleration observer to realize a robust speed control of permanent magnet synchronous motors(PMSM). The proposed speed controller needs the information of the angular acceleration, thus the first-order fuzzy acceleration observer is designed. The LMI existence condition is given for the proposed fuzzy speed controller, and the gain matrices of the controller are calculated. It is verified that the augmented control system consisting of the fuzzy speed controller and the fuzzy acceleration observer is mathematically stable. To validate the effectiveness of the proposed acceleration observer-based fuzzy speed controller, the simulation and experimental results are shown under motor parameter variations. It is definitely proven that the proposed control scheme can precisely track the speed of a permanent magnet synchronous motor.