• Proceedings of the KIEE Conference
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• 1998.11b
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• pp.645-647
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• 1998

A position control algorithm for a inverted pendulum is studied. The proposed algorithm is based on a fuzzy theory and a steady state genetic algorithm(SSGA). The conventional fuzzy methods need expert's knowledges or human experiences. The SSGA, which is a optimization algorithm, tunes the input-output membership parameters and fuzzy rules automatically. The computer simulation to control a inverted pendulum is presented to illustrate the approaches.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.2959-2961
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• 1999

A position control algorithm for a inverted pendulum is studied. The proposed algorithm is based on a fuzzy theory and Generalized Radial Basis Function(GRBF). The conventional fuzzy methods need expert's knowledges or human experiences. The GRBF, which is an optimization algorithm, tunes automatically the input-output membership parameters and fuzzy rules. The simulation is presented to illustrate the approaches.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.35-41
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• 1996

This paper presents a short introduction to fuzzy measures and fuzzy integrals for providing an useful understanding of articles related on fuzzy measure theory and its applications. A brief overview of the basic concepts of systems, models, uncertainty, fuzzy measures and fuzzy integrals is provided. And terminology and notation frequently used in the discussion on the topic are introduced.

• Korean Journal of Remote Sensing
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• v.21 no.2
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• pp.145-162
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• 2005

To improve the accuracy of land-cover discrimination in SAB data classification, this paper presents a methodology that includes feature extraction and fusion steps with multi-temporal SAR data. Three features including average backscattering coefficient, temporal variability and coherence are extracted from multi-temporal SAR data by considering the temporal behaviors of backscattering characteristics of SAR sensors. Dempster-Shafer theory of evidence(D-S theory) and fuzzy logic are applied to effectively integrate those features. Especially, a feature-driven heuristic approach to mass function assignment in D-S theory is applied and various fuzzy combination operators are tested in fuzzy logic fusion. As experimental results on a multi-temporal Radarsat-1 data set, the features considered in this paper could provide complementary information and thus effectively discriminated water, paddy and urban areas. However, it was difficult to discriminate forest and dry fields. From an information fusion methodological point of view, the D-S theory and fuzzy combination operators except the fuzzy Max and Algebraic Sum operators showed similar land-cover accuracy statistics.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.1647-1651
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• 2009

The uncertainty or imprecision associated with vague parameters and weighting sets, reduces the ability to decide what alternative is better for a particular location. To efficiently reduce the effect of imprecision frequently arising in available information, fuzzy theory has been used to improve consideration of imprecision in a Multi-Criteria Decision Analysis (MCDA) problem. Fuzzy logic offers a way to represent and handle imprecision present in continuous real world applications. A GIS implementing fuzzy set theory, (referred to in this paper as the "Spatial Fuzzy Approach") enables decision makers to express imprecise concepts associated with geographic data and provides decision makers the ability to have even more definition and discrimination in terms of the best alternatives for a particular spatial location. This study is focused on addressing questions pertaining to the methodology of floodplain analysis using GIS and Spatial Fuzzy MCDA to evaluate flood damage reduction alternatives. The issues will be examined in a case study of the Suyoung River Basin in Pusan, Korea.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.05a
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• pp.305-308
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• 2003

This paper proposed Ellipsoid Fuzzy-ART (Fuzzy-Adaptive Resonance Theory) for recognition performance improvement to use Mahalanobis distance. The suggested method uses Mahalanobis distance to decide pattern boundary region at vector space. In order to confirm the validity of proposed method, comparison of the performance has made between existing method and the proposed method through simulation.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.1383-1386
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• 1990

Fuzzy theory may be constructed of Fuzzy sets theory, Fuzzy measurement and Appoximate reasoning, and nowadays the reseaches on it are done widely in both theoretical and practical aspects. In this paper, the authors sought for the subject in Hirota's Fuzzy CAI: A decision making simulated fuzzy problem on the speed and accelerator control of a car driven in the high way. Interesting results on these fuzzy solutions of this problem, based on a defuzzification with 9 kinds of the methods, are reported. And the characters of these solutions, linear or nonlinear and their fuzzy control evaluations are stated.

• Transactions of the Korean Society of Automotive Engineers
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• v.8 no.5
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• pp.196-206
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• 2000

These days, the fuzzy logic or the fuzzy set theory has received attention from a number of researchers in the area of industrial application. Moreover, the fuzzy logic control has been successfully applied to a large numbers of control problems where the conventional control methods had failed. Using this control theory we designed a climate controller for an automotive climate control system whose mathematical model is difficult. This paper describes an automotive climate control where the fuzzy control has been used to stabilize parameter uncertainties and disturbance effects. To show the validity and effectiveness of the proposed control method, the fuzzy logic controller was implemented with a philips 80C552 microcomputer chip and tested in an actual vehicle. From the experimental results, it could be conduced that the proposed controller is superior to conventional controllers in both control performance and thermal comfort. The climate control system in cars is difficult to model mathematically so we tested a fuzzy logic control system which promised better results.

• Transactions of the Korean Society of Automotive Engineers
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• v.2 no.5
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• pp.23-29
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• 1994

The design procedure for fuzzy logic controller depends on the expert's knowledge or trial and error. Moreover, it is very difficult to guarantee the stability and robustness of the system due to the linguistic expression of fuzzy control. However, fuzzy logic control has succeeded in many control problems that the conventional control theory has difficulties to deal with. As a result, this control theory is applied to the engine control system which a mathematical model is difficult. In this study, the fuzzy logic is applied to obtain the gain of PI control at idle speed control system, and a simple engine model is developed in order to perform simulation. Experimental results show that the response to reach the target engine speed at idle speed control system is improved by adopting the gain obtained with fuzzy logic.

• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.6
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• pp.605-614
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• 1999

This paper addresses analysis and design of a class of complex single-input single-output fuzzy control systems. In the proposed method, the fuzzy model, which represents the local dynamic behavior of the given nonlinear system, is utilized to construct the controller. The overall controller consists of the local compensators which compensate the local dynamic linear model and the feed-forward controller which is designed via sliding mode control theory. Therefore, the globally stable fuzzy controller is designed without finding a common Lyapunov matrix. and shows improved perfonnance and tracking results by taking the advantages of fuzzy-model-based control theory and sliding mode control theory. Furthennore, stability analysis is conducted not Ibr the fuzzy model but for the real underlying nonlinear system. Two numerical examples are included to show the effcctiveness and feasibility of the proposed fuzzy control method.