• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 하계학술대회 논문집 B
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• pp.974-976
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• 1996

In this paper, a reference model following control system using a fuzzy logic controller(FLC) is proposed By using an integrator and a nonlinear hysteresis element, a reference model whose response has no overshoot and fast rise time is designed. A FLC is designed to follow as close as possible to the response of the reference model. The proposed design method is shown that the robustness and the optimal tracking property can be achieved under modeling error, disturbance and parameter perturbations. The effectiveness of the proposed design method is verified through the simulation that compare using the FLC with using a $H_{\infty}$ controller.

• Journal of Electrical Engineering and Technology
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• 제10권1호
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• pp.118-127
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• 2015

This paper presents an advanced torque ripple minimization method of a switched reluctance motor (SRM) using torque sharing function (TSF). Generally, TSF is applied into the torque control. However, the conventional TSF cannot follow the expected torque well because of the nonlinear characteristics of the SRM. Moreover, the tail current that is generated at a high speed motor drive makes unexpected torque ripples. The proposed method combined TSF with fuzzy logic control (FLC). The advantage of this method is that the torque can be controlled unity at any conditions. In addition, the controller can track the torque under the condition of the wrong TSF. The effectiveness of the proposed algorithm is verified by the simulations and experiments.

• 한국공간구조학회논문집
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• 제21권3호
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• pp.43-50
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• 2021

A tilted tall building is actively constructed as landmark structures around world to date. Because lateral displacement responses of a tilted tall building occurs even by its self-weight, reduction of seismic responses is very important to ensure structural safety. In this study, a smart tuned mass damper (STMD) was applied to the example tilted tall building and its seismic response control performance was investigated. The STMD was composed of magnetorheological (MR) damper and it was installed on the top floor of the example building. Control performance of the STMD mainly depends on the control algorithn. Fuzzy logic controller (FLC) was selected as a control algorithm for the STMD. Because composing fuzzy rules and tuning membership functions of FLC are difficult task, evolutionary optimization algorithm (EOA) was used to develop the FLC. After numerical simulations, it has been seen that the STMD controlled by the EOA-optimized FLC can effectively reduce seismic responses fo the tilted tall building.

• 한국조명전기설비학회:학술대회논문집
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• 한국조명전기설비학회 2007년도 추계학술대회 논문집
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• pp.301-305
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• 2007

This paper is proposed by fuzzy-based MPPT control of photovoltaic to drive induction motor. Design and prototype implement of a fuzzy logic(FL) controller for maxim]m power extraction from a stand-alon photovoltaic Is proposed in this paper. Error and the change of error between maximum power and real power are used by input of fuzzy controller. Moreover, it output changing of voltage from control constant. The validity of this paper is proved by comparing maximum power point tracking and performance of motor drive through comparison fuzzy and PI of tradition method.

• 조명전기설비학회논문지
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• 제25권5호
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• pp.22-33
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• 2011

An induction motor operated with a conventional direct self controller(DSC) shows a sluggish response during startup and under changes of torque command. Fuzzy logic controller(FLC) is used in conjection with DSC to minimize these problems. A FLC chooses the switching states based on a set of fuzzy variables. Flux position, error in flux magnitude and error in torque are used as fuzzy state variables. Fuzzy rules are determinated by observing the vector diagram of flux and currents. This paper proposes hybrid fuzzy controller for direct torque control(DTC) of induction motor drives. The speed controller is based on adaptive fuzzy learning controller(AFLC), which provide high dynamics performances both in transient and steady state response. Flux position, error in flux magnitude and error in torque are used as FLC state variables. The speed is estimated with model reference adaptive system(MRAS) based on artificial neural network(ANN) trained on-line by a back-propagation algorithm. This paper is controlled speed using hybrid fuzzy controller(HFC) and estimation of speed using ANN. The performance of the proposed induction motor drive with HFC controller and ANN is verified by analysis results at various operation conditions.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 하계학술대회 논문집 B
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• pp.567-569
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• 2001

This paper presents improved performance on the speed control of Switched Reluctance Motor(SRM) by using fuzzy logic speed controller. The nonlinear model of SRM is used and the motor used in experiment is a 6/4 SRM. In order to prove the superiority of the fuzzy logic controller, it is applied to make use of Matlab simulation program. And to implement the control method on the SRM drive. DSP(TMS320F240) based SRM speed controller is designed and fabricated. The simulation and experiment results show that FLC is effective in settling time maximum overshoot and torque ripple.

• 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.

• 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.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 G
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• pp.3045-3047
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• 1999

This paper deals with a single flexible link robot system using two fuzzy logic controllers(FLC). The one is used for controlling the rigid position of the beam while it is rotated from one position to another. The other is adopted to reduce the oscillation caused by the rigid body motion. Many simulations are carried out to investigate characteristics of the controlled system. There are good results compared with other systems using PD controller. And also the system could be exactly controlled by the proper setting conditions for FLC.

• 전기학회논문지
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• 제59권5호
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• pp.972-980
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• 2010

In this study, we introduce the design methodology of an optimized type-2 fuzzy cascade controller with the aid of hierarchical fair competition-based genetic algorithm(HFCGA) for ball & beam system. The ball & beam system consists of servo motor, beam and ball, and remains mutually connected in line in itself. The ball & beam system determines the position of ball through the control of a servo motor. Consequently the displacement change of the position of the moving ball and its ensuing change of the angle of the beam results in the change of the position angle of a servo motor. The type-2 fuzzy cascade controller scheme consists of the outer controller and the inner controller as two cascaded fuzzy controllers. In type-2 fuzzy logic controller(FLC) as the expanded type of type-1 fuzzy logic controller(FLC), we can effectively improve the control characteristic by using the footprint of uncertainty(FOU) of membership function. The control parameters(scaling factors) of each fuzzy controller using HFCGA which is a kind of parallel genetic algorithms(PGAs). HFCGA helps alleviate the premature convergence being generated in conventional genetic algorithms(GAs). We estimated controller characteristic parameters of optimized type-2 fuzzy cascade controller applied ball & beam system such as maximum overshoot, delay time, rise time, settling time and steady-state error. For a detailed comparative analysis from the viewpoint of the performance results and the design methodology, the proposed method for the ball & beam system which is realized by the fuzzy cascade controller based on HFCGA, is presented in comparison with the conventional PD cascade controller based on serial genetic algorithms.