• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 B
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• pp.632-634
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• 1998

This paper presents experimental results of the fuzzy controller for DC servo motor. The fuzzy controller consists of 9 quantized levels and 25 fuzzy rules. The fine Controller is employed in the fine control mode when the value of error is between -0.03 and +0.03, whereas the coarse controller is used in the coarse control mode when the value of error is in the outside range of -0.03 and +0.03. The experimental results show that the fuzzy controller provides a better performance (lower overshoot and error) than the PID controller regardless of the load applied.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1995년도 하계학술대회 논문집 B
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• pp.717-719
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• 1995

In this paper, we analyze the effects of scaling factors on the performance of a fuzzy controller and propose the tuning method for them. The quantitative relation between input and output variables of a fuzzy controller is obtained by using a quasi-linear fuzzy model. An approximate transfer function of a fuzzy controller is derived from the comparison a fuzzy controller with the conventional PID controller. We analyze the effects of scaling factor using this approximate transfer function and propose a fuzzy tuning method based on that of Maeda et al[4].

• 대한전기학회:학술대회논문집
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• 대한전기학회 1995년도 하계학술대회 논문집 B
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• pp.830-832
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• 1995

A position Control algorithm of the flexible manipulator is studied. The proposed algorithm is based on a Fuzzy Logic Control(FLC) method using the human's experiences. FLC does not need a dynamic modeling of a flexible manipulator. A Fuzzy logic controller is designed that the end-point of the flexible manipulator tracks the desired trajectory. The control input to the process is determined by the error and variation of error. Simulation result shows a robustness of FLC compared with the PID control algorithm.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1995년도 하계학술대회 논문집 B
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• pp.852-854
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• 1995

This paper proposes a new identification method that utilizes fuzzy inference in parameter identification. The prosed system has an additional control loop where a real plant has replaced by a plant model. Fuzzy rules describe the relationship between comparison results of the features and magnitude of modification in the model parameter values. In this paper, the tuning method which determines parameters of PID controller automatically is described through applying this algorithm to DC servo motor. And we intend to investigate effectiveness of the method by experiments. This method is effective in auto-tuning because the response of the closed loop has verified. The simulated and the experimental results of the dc servo motor are shown to confirm the viability of this method.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 하계학술대회 논문집 B
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• pp.1323-1326
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• 1996

This paper describes an air conditioner control method using a fuzzy control theory. The fuzzy control method was implemented with Philips 80C552 one chip microcomputer and tested in an actual vehicle. Experiments showed that proposed control method is superior to the conventional PID control method especially in the environments with abrupt disturbance and parameter variation of the control system. Fuzzy-Based control method was proved to maintain a stable and improved temperature control in an abrupt environmental changes.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 하계학술대회 논문집 B
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• pp.1024-1026
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• 1996

Sources of nonlinearity In a fuzzy logic controller Include the fuzzification, the fuzzy reasoning and the defuzzification. In this paper, a closed form expression for the defuzzified output is derived in case of a fuzzy logic controller with two Inputs, triangular memberships, MacVicar-Whelan type linguistic rules, and direct fuzzy reasoning. As a result, it is shown that fuzzy logic controller is a nonlinear controller. Also its nonlinearity Is analyzed with respect to the conventional PID control and the sliding mode control.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1993년도 하계학술대회 논문집 A
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• pp.316-318
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• 1993

In order to estimation the optimum PID parameter of the turbine speed controller, the response cure of the object plant was compared with the reference pattern and then the magnitude peak value error and peak time error was calculated. With the calculated errors as input into the Fuzzy inference Method was introduced to propose the tuning method for each parameter. And the computer simulation was performed with the above Fuzzy inference method in which the Chunju hydro power plant turbine governor system was used as a model. This Study also aims to develop the exclusive tuner for govenor using industrial computer.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 춘계학술대회 논문집 전기기기 및 에너지변환시스템부문
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• pp.248-252
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• 2003

This paper has a control method proposed for the effective self-tuning fuzzy speed control based on neural network of the induction motor indirect vector control. The vector control of an induction motor provides the decoupled control of the rotor flux magnitude and the torque producing current to performance is desirable. But, the drive performance often degrades for the machine parameter variations and its condition give rise to coupling of flux and torque current. The fuzzy speed control of an induction motor has the robustness about machine parameter variations compared with conventional PID speed control in a way. That proved to be some waf from the true. The purpose of this paper is to improve the adaptation by offering self-turning function to fuzzy speed controller. In this paper, the adaptive mechanism of fuzzy speed control in used ANN(Artificial Neural Network) technique is applied in an IFO induction machine drive, such that the machine can follow a reference model (an ideal field oriented machine) to achieve desired speed. In this paper proved the self-turning method of fuzzy controller has the robustness about parameter variation and the wide range of adaptation by simulation.

• 한국정밀공학회지
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• 제28권11호
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• pp.1265-1271
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• 2011

These days the number of aged and disabled people is increasing rapidly. But most of the disabled or the aged who have the ability to work, want to engage in economic activities and solve social restrictions as well as their bad financial conditions. This paper concerns about the tracking control of an electric wheelchair robot for welfare vehicle where the seat and electric wheelchair are separated and electric wheelchair robot must be autonomously controlled without the help of assistant. So the aged or the disabled people can drive welfare vehicle by himself by adopting this system. Therefore the concept of both an autonomous driving of electric wheelchair and path tracking robots is required in this system. Finally we suggested fuzzy controller in order to control the path tracking of electric wheelchair robot and compared the capability of the proposed controller with conventional PID controller.

• 한국자동차공학회논문집
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• 제16권4호
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• pp.159-164
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• 2008

In diesel engine technology the drive to reduce emissions and fuel consumption with improved performance targets has led to many advances. In particular, Exhaust Gas Recirculation (EGR) and Variable Geometry Turbocharger (VGT) have played a key role in achieving these aims by permitting flexible control of the engine inlet gas charge. The full potential of these devices are difficult to achieve due to limitations in the classical control methods. However, fuzzy logic is particularly appealing due to its simple heuristic nature. The controller used in this work was designed using the Matlab Fuzzy Logic Toolbox. The overall object is to access the potential for emissions and fuel consumption reductions during transient events whilst maintaining and even improving driveability. Classical control methods (PID), as used on production engines, are examined and contrasted with an coordinated control that utilizes fuzzy logic.