• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1931-1932
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• 2008

To demonstration the efficiency of fuzzy logic controller, we carried out simulation with a automobile's transfer function. First, we designed the PID controller by using Ziegler-Nichols tunning method. Second, we calculated time response for each controller, then we compared the speed patterns of fuzzy controlled system and PID controlled system. Also we compared the difference of input variable. By comparing two controller's response, we can confirm the merit of fuzzy controller about comfortability. Fuzzy controller can reduce input changing frequency.

• Journal of the Korean Operations Research and Management Science Society
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• v.18 no.2
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• pp.23-43
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• 1993

This paper employs fuzzy variables instead of deterministic variables for job times in a project network. A fuzzy variable has its value restricted by a possibility distribution. This paper utilizes the triangular possibility distribution which has three estimated times. That is normal, resonable, and crash job times. This paper develops a fuzzy k-longest path algorithm, by utilizing the k-longest path algorithm. This algorithm will be useful to control the project the project network by considering the project completion possibility.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.348-348
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• 2000

In this paper, we present a fuzzy moving sliding mode control for two-degrree-of-freedom robotic manipulator. 17he sliding surface parameters are designed by fuzzy inference. The proposed sliding mode control makes the error always remain on the surface from beginning and therefore, the system is insensitive to system uncertaintics and external disturbances. Simulation results show the effectiveness of proposed scheme.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.134-134
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• 2000

A switching control using multiple gains in the fuzzy rule is newly proposed for an abruptly changing hydraulic servo system. The proposed scheme employs fuzzy PID control, where modified input parameters are used, and LVQNN(Learning Vector Quantization Neural Network) as a switching controller (supervisor). Simulation and experimental studies have been carried out to validate and illustrate the proposed controller.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.11a
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• pp.73-76
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• 1997

This paper proposes the fuzzy logic-based fast gain scheduling(FFGS) controller for regulation problem in nonlinear systems. It utilizes which reflects the derivative information on the original scheduling variable in order to achieve better performance than the existents. Moreover, we apply the proposed control scheme to control active suspension systems with nonlinear components.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.37-40
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• 2002

In this paper, we introduce the concepts of m-convex and pseudo-m-convex for fuzzy mappings of one variable on the notion of differentiability proposed by Goeschel and Voxman, and investigate the relationship between m-convex fuzzy mappings and pesudo-m-convex fuzzy mappings.

• Journal of Welding and Joining
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• v.28 no.6
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• pp.76-83
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• 2010

The purpose of this study is to propose a method to decide near-optimal settings of the constant current fuzzy control parameters using a controlled random search. This method tries to find the near-optimal settings of the constant current fuzzy control parameters through experiments. It has an advantage of being able to carry out searches in the search domain which includes some irregular points. The method suggested in this study was used to determine the fuzzy control parameters by which the desired welding current were formed during inverter DC resistance spot welding. The output variable was the ITAE (integral of time multiplied by the absolute error). This output variable was determined according to the input variables, which are the GE, GDE, and GDU. This study described how to obtained near-optimal welding current condition over a wide search space conducting a relatively small number of experiments.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.1
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• pp.22-28
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• 2014

This paper proposes the fuzzy modeling and robust stability analysis of wind farm based on prediction model for wind speed. Owing to the sensitivity of wind speed, it is necessary to study the dynamic equation of the variable speed wind turbine. In this paper, based on the least-square method, the wind speed prediction model which is varied by the surrounding environment is proposed so that it is possible to evaluate the practicability of our model. And, we propose the composition of intelligent wind farm and use the fuzzy model which is suitable for the design of fuzzy controller. Finally, simulation results for wind farm which is modeled mathematically are demonstrated to visualize the feasibility of the proposed method.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.3
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• pp.182-187
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• 2007

A fuzzy modeling method is proposed to build the dynamic model of a walking-beam reheating furnace from the recorded data. In the proposed method, the number of membership function on each variable is increased individually and the modeling accuracy is evaluated iteratively. When the modeling accuracy is satisfied, the membership functions on each variable are fixed and the structure of fuzzy model is determined. Because the training data is limited, in this process, as the number of membership function increase, it is highly possible that some rules are missing, i.e., no data in the training set corresponds to the consequent part of a missing rule. To complete the rulebase, the output of the model constructed at the previous step is used to generate the consequent part of the missing rules. Finally, in the real time application, a rolling update scheme to rulebase is introduced to compensate the change of system dynamics and fine tune the rulebase. The proposed method is verified by the application to the modeling of a reheating furnace.

• Nuclear Engineering and Technology
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• v.54 no.7
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• pp.2435-2443
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• 2022

The once-through steam generator used in the small modular reactor needs to consider the stability of the outlet steam pressure and steam superheat of the secondary circuit to achieve better operating efficiency. For this reason, this paper designs a controllable operation scheme for the steam pressure and superheat of the small reactor once-through steam generator. On this basis, designs a variable universe fuzzy controller, first, design the fuzzy control rules to make the controller adjust the PI controller parameters according to the change of the error; secondly, use the domain adjustment factor to further subdivide the input and output domain of the fuzzy controller according to the change of the error, to improve the system control performance. The simulation results show that the operation scheme proposed in this paper have better system performance than the original scheme of the small reactor system, and controller proposed in this paper have better control performance than traditional PI controller and fuzzy PI controller, what's more, the designed control system also showed better anti-disturbance performance in lifting experiment between 100% and 80% working conditions. Finally, the experimental platform formed by connecting the digital small reactor with Matlab/Simulink through OPC(OLE for Process Control) communication technology also verified the feasibility of the proposed scheme.