• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2006.05a
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• pp.309-314
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• 2006

Interior permanent magnet synchronous motor(IPMSM) has become a popular choice in electric vehicle applications, due to their excellent power to weight ratio. This paper proposes maximum torque control of IPMSM drive using adaptive learning fuzzy neural network and artificial neural network. This control method is applicable over the entire speed range which considered the limits of the inverter's current md voltage rated value. For each control mode, a condition that determines the optimal d-axis current $i_d$ for maximum torque operation is derived. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using adaptive teaming fuzzy neural network and artificial neural network. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper proposes speed control of IPMSM using adaptive teaming fuzzy neural network and estimation of speed using artificial neural network. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The proposed control algorithm is applied to IPMSM drive system controlled adaptive teaming fuzzy neural network and artificial neural network, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper proposes the analysis results to verify the effectiveness of the adaptive teaming fuzzy neural network and artificial neural network.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.524-528
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• 1996

Quality information is known to have the characteristic of continuous distribution in many manufacturing processes. It is difficult to describe the process condition by classifying the distribution into discrete ranges which is based on the set concept. Fuzzy control chart has been developed for the control of linguistic data but it still utilizes the dichotomous notion of classical set theory. In this paper, the fuzzy sampling method is studied in order to manage the ambiguous data properly and incorporated for generating fuzzy control chart. The method is based on the fuzzy set concept and considered to be appropriate for the realization of a complete fuzzy control chart. The fuzzy control chart was compared with the conventional generalized p-chart in the sensitivity for quality distribution and robustiness against the noise. The fuzzy control chart with the fuzzy sampling method showed better characteristics.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.3
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• pp.917-926
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• 2013

This study presents the feasibility of fuzzy multi-criteria decision making (MCDM) techniques for the robust prioritization of projects. It is applied to water resources planning problem. Results from weighted sum method (WSM), analytic hierarchy process (AHP), revised analytic hierarchy process (R-AHP), and TOPSIS are compared with those from Fuzzy WSM, Fuzzy, AHP, Fuzzy R-AHP, and Fuzzy TOPSIS. For the calculation, all weights on criteria and the normalized data were obtained from the same investigation. As a result, the rankings from four MCDM techniques are slightly different while those from fuzzy MCDM show the comparatively consistent ranking. Therefore, it is desirable to use fuzzy MCDM technique when MCDM is used for the prioritization problem, since fuzzy MCDM can include the uncertain variability of input data and weighting values on criteria.

• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.4
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• pp.384-388
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• 1999

This paper describes an approach for synthesizing a modularized gain scheduled PD type fuzzy logic controller(FLC) of nonlinear magnetic bearing system where the gains of FLC are on-line adapted according to the operating point. Specifically the systematic procedure via root locus technique is carried out for the selection of the gains of FLC. Simulation results demonstrate that the proposed gain scheduled fuzzy logic controller yields not only maximization of stability boundary but also better control performance than a single operating point (without gain scheduling)fuzzy controller.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.922-927
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• 1991

This study is aimed to investigate a design problem of the fuzzy logic controller for the activated sludge process(ASP) in sewage treatment. The modeling technique proposed by Sugeno is used to express the ASP effectively and identification of a fuzzy model of the ASP is carried out utilizing actual operational data obtained from a metropolitan sewage plants. The model-based fuzzy controller is designed by rules generated from the identified ASP fuzzy model. Feasibility of the designed controller is tested through computer simulations.

• Journal of the Earthquake Engineering Society of Korea
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• v.8 no.4
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• pp.51-62
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• 2004

Fuzzy supervisory control technique for the seismic response control of cable-stayed bridges subject to earthquakes is studied. The proposed technique is a hybrid control method, which adopts a hierarchical structure consisting of several sub-controllers and a fuzzy supervisor. Sub-controllers are independently designed to reduced the responses to be controlled of a cable-stayed bridge, and a fuzzy supervisor achieves improved seismic control performance by tuning the pre-designed sub-controllers. It is realized by converting static gains of the sub-controllers into time-varying dynamic gains through the fuzzy inference mechanism. To evaluate the feasibility of the proposed technique, the benchmark control problem of cable-stayed bridge proposed by Dyke et al. is adopted. The control variables for the seismic response control of the cable-stayed bridge are determined to be t도 shear forces and bending moments at the base of the towers, the longitudinal displacements at the top of the towers, the relative displacements between the deck and the tower, and the tensions in the stay cables. Comparative results between the fuzzy supervisory controller and LQG controller demonstrate the effectiveness of the proposed control technique.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.15 no.3
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• pp.57-66
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• 2001

This paper resents a control approach for designing a fuzzy-PI controller for a synchronous generator excitation and SVC system A combination of thyristor-controlled reactors and fixed capacitors (TCR-FC) type SVC is recognized as having the must fiexible control and high speed response, which has been widely utilized in power systems, is considered and designed to improve the response of a synchronous generator, as well as controlling the system voltage A Fuzzy-PI controller for SVC system was proposed in this paper. The PI gain parameters of the proposed Fuzzy-PI controller which is a special type of PI ones are self-tuned by fuzzy inference technique. It is natural that the fuzzy inference technique should be barred on humans intuitions and empirical knowledge. Nonetheless, the conventional ones were not so. Therefore, In this paper, the fuzzy inference technique of PI gains using MMGM(Min Max Gravity Method) which is very similar to humans inference procedures, was presented and allied to the SVC system. The system dynamic responses are examined after applying all small disturbance condition.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.20 no.3
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• pp.273-282
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• 2002

Although the influence of GIS has been proved in a variety of applications, there also have been some research issues about that the coupling of GIS with other mathematical or engineering tools is necessary to meet various needs of specialized problem domains. Linear Programming, a mathematical technique used in optimal distribution of given quantity, can enhance its usability by integrating with GIS since LP basically does not include means to deal with spatial data. The limitation of the traditional LP technique is that it requires explicitly defined conditions, which is impractical or impossible in such decision making processes as in land use problems that use less crisp decision factors. This study develops a method to incorporate such fuzzy situations by integrating Fuzzy-LP that employs fuzzy logic and GIS. The GIS provides data to or displays data from the Fuzzy-LP processes in the integrated system. This methodology is illustrated to solve a land use distribution problem.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.12 s.189
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• pp.46-55
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• 2006

A robust motion controller based on self-organizing fuzzy control(SOFC) and feed-back tracking control technique is proposed for a two-wheel driven mobile robot. The feed-back control technique of the controller guarantees the robot follows a desired trajectory. The SOFC technique of the controller deals with unmodelled dynamics of the vehicle and uncertainties. The computer simulations are carried out to verify the tracking ability of the proposed controller with various driving situations. The results of the simulations reveal the effectiveness and stability of the proposed controller to compensate the unmodelled dynamics and uncertainties.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.276-278
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• 2009

In this paper, we propose the smart management technique of applications using fuzzy logic in wireless sensor networks. We consider the intelligent action compared to the classical action that can only be controlled by on and off. The vagueness depends on the places of the sensor nodes, human's character and emotion. In order to control them with the smartness, the proposed technique considers the better performance of applications in wireless sensor networks. We performed the simulations and implementations on sensor nodes and checked out our ideas. The simulation results show that the proposed technique is more reasonable than the classical approach.