• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 하계학술대회 논문집 D
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• pp.2064-2066
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• 2002

This paper proposes Model Reference Adaptive Fuzzy System(MRAFS) using Fuzzy Logic Controller(FLC) as a adaptive laws in Model Reference Adaptive System(MRAS) in order to realize the speed-sensorless control of an induction motor. MRAFS estimates the speed of an induction motor with a rotor flux of a reference model and adjustable model in MRAS. Fuzzy logic controller reduces the error of the rotor flux between the reference model and the adjustable model using the error and the change of error as the input of FLC. The computer simulation is executed to verify the propriety and the effectiveness of the proposed system.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 A
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• pp.37-39
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• 2000

This paper describes the application of Fuzzy Logic Controller (FLC) to Thyristor Controlled Series Capacitor (TCSC) which can have significant impact on Power system dynamics. The function of the FLC is to control the firing angle of the TCSC. We tuned the scaling factors of the FLC using Tabu Search. The proposed FLC is used for damping the low frequency oscillations caused by disturbances such as the sudden changes of small of large loads or the outages in the generators or transmission lines. To evaluate usefulness of the proposed FLC. we performed the computer simulation for single-machine infinite system. The response of FLC is compared with that of PD controller optimized using Tabu Search. Simulation results that the FLC shows the better control performance than PD controller.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 D
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• pp.2763-2765
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• 2000

The interactions between the excavation tool and the excavation environment are dynamic, unstructured and complex. In addition. operating modes of an excavator depend on working conditions, which makes it difficult to derive the exact mathematical model of excavator. Even after the exact mathematical model is established, it is difficult to design of a controller because the system equations are highly nonlinear and the state variable are coupled. The objective of this study is to design a fuzzy logic controller (FLC) which controls the position of excavator's attachment. This approach enables the transfer of human heuristics and expert knowledge to the controller. Expeiments are carried out to check the performance of the FLC.

• 제어로봇시스템학회논문지
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• 제15권5호
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• pp.525-529
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• 2009

Most of FLC received input data from error e and change-of-error e' with no relation with system complexity. Basic scheme follows typical PD and PI or PID Controller and that has been developed through fixed ME In this paper, We studied the relationship between MF and system response and system response through changing Fuzzy variable of consequence MF and propose the simple FLC using this relationship. The response of FLC is changed according to the width of Fuzzy variable of consequence MF. As changing the Fuzzy variable of consequence MF shows various nonlinear characteristic, we studied the relation between response and MF using analytical method. We designed the effective FLC using three-variable MF and nine rules and took simulation for verification. In this study, we propose the method to design system with FLC in stability point which is an impotent characteristic of designing system. The circle criterion which is adapted to analysis the nonlinear system is put to use for proposed method. Since SISO FLC has a time-invariant and odd characteristic we can use the critical point not disk which is generally used to determine the stability in the circle criterion, to determine the stability. Using this, we can get the maximum critical point plot of SISO FLC with changing the consequence fuzzy variables. The predetermined critical point plot of FLC can be used to decide the region of the system to be stable. This method is effectively used to design the SISO FLC.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.863-868
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• 1992

This paper presents a method on applying Genetic Algorithm(GA), which is a well-known high performance optimizing algorithm, to construct the self-organizing fuzzy logic controller. Fuzzy logic controller considered in this paper utilizes Sugeno's hybrid inference method, which has an advantage of simple defuzzification process in the inference engine. Genetic algorithm is used to find the optimal parameters in the FLC. The proposed approach will be demonstrated using 2 d.o.f robot manipulator to verify its effectiveness.

• 한국지능시스템학회논문지
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• 제2권3호
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• pp.58-67
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• 1992

This paper presents a method on applying Genetric Algorithms(GA), which is a well-know high performance optimizing algorithm, to construct the self-organizing fuzzy logic controller. Fuzzy logic controller considered in this paper utilized Sugeno's hybrid inference method. which has an advantage of simple defuzzification process in the inference engine. Genetic algorithm is used to find the iptimal parameters in the FLC. The proposed approach will be demonstrated using 2 d. o. f robot manipulator to verify its effectiveness.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 심포지엄 논문집 정보 및 제어부문
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• pp.30-32
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• 2005

Mobility of an indoor wheeled robot is affected by adhesion force that is related to various floor conditions. When the adhesion force between driving wheels and floor decreases suddenly, the robot begins slip. In order to overcome this slip problem, optimal slip velocity must be decided for stable movement of wheeled robot. First of all, this paper shows that conventional PI control can not be applied to a wheeled robot of the light weight. Secondly, proposed fuzzy logic is applied to the Takagi-Sugeno model for the configuration of fuzzy sets. For the design of Takagi-Sugeno model and fuzzy rule, proposed algorithm uses FCM(Fuzzy c-mean clustering method) algorithm. The proposed fuzzy logic controller(FLC) is pretty useful with prevention of the slip phenomena for the controller performance in the re-adhesion control strategy.

• 전자공학회논문지C
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• 제34C권7호
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• pp.38-50
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• 1997

This paper concerns a VHDL design and simulation of an accurate and cost-effective fuzzy logic controller (FLC). The accurcy of the proposed FLC is obtained by using the center of gravity (COG) defuzzifier that considers both membership values and spans of membership functions in calculating a crisp value. The cost-effectiveness of the proposed FLC is obtained by restructuring the conventional FLC in the following ways: Firstly, the MAX-MIN inference is inference is replaced by a read-modify-write operation that can be implemented economically in the structure of register files. Secondly, the division in the COG defuzzifier is avoided by finding the moment equilibrium point. The proposed COG defuzzifier has two disadvantages that it requires additional multipliers and it takes a lot of computation time to find the moment equilibrium point. The first disadvantage is overcome by replacing the mulitpliers with stochastic AND operations and the second disadvantage is alleviated by using a coarse-to-fine searching algorithm. The proposed FLC is described in VHDL structurally and behaviorally and whether it is working well or not is checked on SYNOPSYS VHDL simulator by using the truck backer-upper control problem.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2004년도 전력전자학술대회 논문집(2)
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• pp.655-659
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• 2004

This paper proposes a fuzzy logic based vector control for the gearless traction machine drive systems using a permanent-magnet synchronous motor (PMSM). The performance of the proposed Fuzzy Logic Control(FLC)-based PMSM drive are investigated and compared to those obtained from the conventional PI controll-based drive system. We have confirmed theoretically and experimentally at different dynamic operating conditions such as step change in command speed, step change in load, etc. The comparative experimental results show that the FLC is more robust and, hence, found to be a suitable replacement of the conventional Pl controller for the high-performance elevator drive system.

• International Journal of Computer Science & Network Security
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• 제21권5호
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• pp.175-182
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• 2021

The greenhouse is a complex system. It is subject to multiple input disturbances that are highly dependent on meteorological conditions, which are generally nonlinear and have a great influence on the agricultural production. The objective of this paper is to study the fuzzy logic technique as one of the most efficient technologies to control the greenhouse. The fuzzy logic controller (FLC) was developed to activate the actuator based on a ventilator was installed in an experimental greenhouse to obtain a desired temperature of the microclimate despite the externals disturbances.