• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.184-187
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• 1996

In this paper, an algorithm for tuning gains of a PID controller is proposed. The proposed algorithm is composed of two stages. The first is a stage for Lyapunov function-based initial stabilization of an overall system and rough tuning gains of the PID controller. The other is that for fine tuning gains of the PID controller. All tunings are performed by using the well-known fuzzy logic-based tuner. The computer simulations are performed to show the validity of the proposed algorithm and results are presented.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.825-829
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• 2005

This paper presents an approach for designing a fuzzy logic-based adaptive SVC damping In controller for damping low frequency power oscillations. Power systems are often subject to low Frequency electro-mechanical oscillations resulting from electrical disturbances. Generally, power system stabilizers are designed to provide damping against this kind of oscillations. Another means to achieve damping is to design supplementary damping controllers that are equipped with SVC. Various approaches are available for designing such controllers, many of which are based on the concepts of damping torque and others which treat the damping controller design as a generic control problem and apply various control theories on it. In our proposed approach, linear optimal controllers are designed and then a fuzzy logic tuning mechanism is constructed to generate a single control signal. The controller uses the system operating condition and a fuzzy logic signal tuner to blend the control signals generated by two linear controllers, which are designed using an optimal control method. First, we design damping controllers for the two extreme conditions; the control action for intermediate conditions is determined by the fuzzy logic tuner. The more the operating condition belongs to one of the two fuzzy sets, the stronger the contribution of the control signal from that set in the output signal. Simulation studies done on a one-machine infinite-bus and a four-machine two-area test system, show that the proposed fuzzy adaptive damping SVC controller effectively enhances the damping of low frequency oscillations.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.28B no.11
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• pp.941-954
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• 1991

The characteristics of a power plant changes as it operates for a long time and/or for different operating point. As a result, operators must retune gains of the controllers for better performance. In fact, skilled operators can retune the gains in reference to recorded data obtained by a test called dynamic test. The dynamic test, however, requires much time, and can be heavy burden for operators. In this paper, an expert knowledge-based auto-tuner is designed for drum-type boiler controllers of a fossil power plant using fuzzy logic. The performance of the proposed auto-tuner is shown via computer simulation and the simulation results show that the proposed auto-tuner is satisfactory for the desired performance.

• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.3
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• pp.64-72
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• 1995

This paper proposes how to tune the gains of PI controllers in case of gain change in a process control system. Controllers of PI type have been used in industry and the gains of the controllers have been tuned by expert engineers. It, therefore, takes much time and efforts to tune the controllers. It is more difficult to find gains of multi-loop processes. The tuning method of a fuzzy tuner in this paper is developed based on the assumptions that the PI controllers are of analog type and are tuned off-line, and that the characteristic values must be supplied for the tuner. A Tuner using Fuzzy Logic(FLT1 is capable of showing presentlpast states of a process control system and finding gains of PI controllers. The verfication of the FLT is shown by various experiments.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.704-707
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• 1997

In this paper, we present a fuzzy logic based tuner for continuous on-line tuning of PID controllers. The essential idea of the scheme is to parameterize a Ziegler-Nichols-like tuning formula by a singler parameter .alpha., then to use an on line fuzzy logic to self-tune the parameter. The adaptive scaling makes the controller robust against large variations in parametric and dynamics uncertainties in the plant model. New self-tuning controller has the ability to decide when to use PI or PID control by extracting process dynamics from relay experiments. These scheme lead to improved performance of the transient and steady state behavior of the closed loop system, including processes with nonminimum phase processes.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.219-225
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• 1991

The characteristics of a power plant changes as it operates for a long time and/or for different operating points. As a result, operators must retune gains of the controllers for better performance. In fact, skilled operators can retune the gains in reference to recorded data obtained by a test called dynamic test. The dynamic test, however, requires much time, and can be heavy burden for operators. In this paper, an expert knowledge-based auto-tuner is designed for drum-type boiler controllers of a fossil power plant using fuzzy logic. The performance of the proposed auto-tuner is shown via computer simulation and the simulation results show that the proposed auto-tuner is satisfactory for the desired performance.

• Journal of Electrical Engineering and Technology
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• v.13 no.1
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• pp.451-459
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• 2018

This work presents an approach for modeling of electric vehicle considering the vehicle dynamics, drive train, rotational wheel and load dynamics. The system is composed of IPMSM (Interior Permanent Magnet Synchronous Motor) coupled with the wheels through a drive train. Generally, IPMSM is controlled by ordinary PID controllers. Performance of the ordinary PID controller is not satisfactory owing to the difficulties of optimal gain selections. To overcome this problem, a new type of fuzzy logic gain tuner for PID controllers of IPMSM is required. Therefore, in this paper fuzzy logic based gain tuning method for PID controller is proposed and compared with some previous control techniques for the better performance of electric vehicle with an optimal balance of acceleration, speed, travelling range, improved controller quality and response. The model was developed in MATLAB/Simulink, simulations were carried out and results were observed. The simulation results have proved that the proposed control system works well to remove the transient oscillations and assure better system response in all conditions.

• Proceedings of the IEEK Conference
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• 2003.07d
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• pp.1295-1298
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• 2003

The steam generator level in a PWR is very difficult to control particularly at low power. And the constant control gain and time value are not adaptive in steam generator level controller. In normal operation constant control gain and time value have no problem. But there is problem at low power. So variable control gains based on the temperature are required. The best control gain is decided by the experienced knowledge. A fuzzy gain tuner is used for the gain tuning. In the design of fuzzy gain-tuner processing, the experienced knowledge is employed for making fuzzy rules.

• Journal of Korean Society of Environmental Engineers
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• v.22 no.10
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• pp.1905-1919
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• 2000

The main motivation of this research is to develop an intelligent control strategy for Activated Sludge Process (ASP). ASP is a complex and nonlinear dynamic system because of the characteristic of wastewater, the change in influent flow rate, weather conditions, and etc. The mathematical model of ASP also includes uncertainties which are ignored or not considered by process engineer or controller designer. The ASP is generally controlled by a PID controller that consists of fixed proportional, integral, and derivative gain values. The PID gains are adjusted by the expert who has much experience in the ASP. The ASP model based on $Matlab^{(R)}5.3/Simulink^{(R)}3.0$ is developed in this paper. The performance of the model is tested by IWA(International Water Association) and COST(European Cooperation in the field of Scientific and Technical Research) data that include steady-state results during 14 days. The advantage of the developed model is that the user can easily modify or change the controller by the help of the graphical user interface. The ASP model as a typical nonlinear system can be used to simulate and test the proposed controller for an educational purpose. Various control methods are applied to the ASP model and the control results are compared to apply the proposed intelligent control strategy to a real ASP. Three control methods are designed and tested: conventional PID controller, fuzzy logic control approach to modify setpoints, and fuzzy-PID control method. The proposed setpoints changer based on the fuzzy logic shows a better performance and robustness under disturbances. The objective function can be defined and included in the proposed control strategy to improve the effluent water quality and to reduce the operating cost in a real ASP.