• Structural Engineering and Mechanics
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• v.22 no.4
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• pp.469-481
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• 2006

A new method called fuzzy factor method for the stationary stochastic response analysis of fuzzy truss with global fuzzy structural parameters is presented in this paper. Considering the fuzziness of the structural physical parameters and geometric dimensions simultaneously, the fuzzy correlation function matrix of structural displacement response in time domain is derived by using the fuzzy factor method and the optimization method, the fuzzy mean square values of the structural displacement and stress response in the frequency domain are then developed with the fuzzy factor method. The influences of the fuzziness of structural parameters on the fuzziness of mean square values of the displacement and stress response are inspected via an example and some important conclusions are obtained. Finally, the example is simulated by Monte-Carlo method and the results of the two methods are close, which verified the feasibility of the method given in this paper.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.177-177
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• 2000

In this paper, we propose a two-input two-output fuzzy controller to improve the performance of transient response and to eliminate the steady state error. The outputs of this controller are the control input calculated by position-type fuzzy controller and the accumulated error scaling factor. Here, the accumulated error scaling factor is adjusted on-line by fuzzy rules according to the current trend of the controlled process. To show the usefulness of the proposed controller, it is applied to several systems that are difficult to get satisfactory response by conventional PD controllers or PI controllers.

• The Journal of Korea Robotics Society
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• v.2 no.3
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• pp.212-220
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• 2007

This paper proposes a method of avoiding obstacles and tracking a moving object continuously and simultaneously by using new concepts of virtual tow point and fuzzy danger factor for differential wheeled mobile robots. Since differential wheeled mobile robot has smaller degree of freedom to control and are non-holonomic systems, there exist multiple solutions (trajectories) to control and reach a target position. The paper proposes 'fuzzy danger factor' for obstacles avoidance, 'virtual tow point' to solve non-holonomic object tracking control problem for unique solution and three kinds of fuzzy logic controller. The fuzzy logic controller is policy decision controller with fuzzy danger factor to decide which controller's result is more valuable when the mobile robot is tracking a moving object with obstacles to be avoided.

• Journal of the Korean Society of Clothing and Textiles
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• v.20 no.2
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• pp.362-372
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• 1996

Recently, need for the development of the quantification of subjective evaluation is growing for the production of high-touch and high-tech textile products. In this study, Fuzzy theory is utilized for the evaluation of the wear comfort of the various blouses. Result of a new evaluation method and factor scores, validity of the new evalution technique adopted fuzzy theory was crosschecked with the results of fator analysis and factor scores. As results, fuzzy theory was proved to be adequate methodology to objectify the subjective evaluation of the adequacy of clothing which is worn. When DUNCAN'S multiple comparion among median of the fuzzy composite score were compared with the results of factor score, the sensitivity of the test methods tends to increase. Therefore, it is suggested that fuzzy weighted checklist is an alternative evaluation scale for the subjective comparison of the textile products. In addition, individual median of fuzzy composite score value should be treated by statistical for the sensitive analysis of subjective evalution.

• Proceedings of the Korea Concrete Institute Conference
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• 1992.10a
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• pp.240-244
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• 1992

The values of a linguistic variable are words, phrases, or sentences in a given language. For example, structural damage can be considered as linguistic variable with values such a 'severely damaged', 'moderately damaged', which are meaningful classifications but not clearly defined, This paper is to evaluate reasonably the correction factor of bridge capacity with the aid of fuzzy sets theory. By using the above mentioned fuzzy measure, the concept of fuzzy integral and linear membership function can be defined. It is concluded that the fuzzy sets theory cam be applied to determine reasonably the correction factor of bridge capacity.

• Proceedings of the KIPE Conference
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• 2001.07a
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• pp.268-271
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• 2001

This paper describes the power factor control of doubly fed induction machine using fuzzy logic algorithm in wind power generation system. Under fuzzy logic control, which enables superior dynamic performance, the power factor is independently controllable by decoupled d, q rotor experimental results are presented.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.6
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• pp.789-799
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• 1999

In this paper, the optimization of fuzzy inference systems is proposed for fuzzy model of nonlinear systems. A fuzzy model needs to be identified and optimized by means of the definite and systematic methods, because a fuzzy model is primarily acquired by expert's experience. The proposed rule-based fuzzy model implements system structure and parameter identification using the HCM(Hard C-mean) clustering method, genetic algorithms and fuzzy inference method. Two types of inference methods of a fuzzy model are the simplified inference and linear inference. in this paper, nonlinear systems are expressed using the identification of structure such as input variables and the division of fuzzy input subspaces, and the identification of parameters of a fuzzy model. To identify premise parameters of fuzzy model, the genetic algorithms is used and the standard least square method with the gaussian elimination method is utilized for the identification of optimum consequence parameters of fuzzy model. Also, the performance index with weighting factor is proposed to achieve a balance between the performance results of fuzzy model produced for the training and testing data set, and it leads to enhance approximation and predictive performance of fuzzy system. Time series data for gas furnace and sewage treatment process are used to evaluate the performance of the proposed model.

• Journal of Power System Engineering
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• v.2 no.3
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• pp.21-26
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• 1998

Numerical simulations for various fluid flows require enormous computing time during iterations. In order to solve this problem, several techniques have been proposed. A SOR method is one of the effective methods for solving elliptic equations. However, it is very difficult to find the optimum relaxation factor, the value of this factor for practical problems used to be estimated on the basis of expertise. In this paper, the implication of the relaxation factor are translated into fuzzy control rules on the basis of the expertise of numerical analysers, and fuzzy controller incorporated into a numerical algorithm. From two cases of study, Poisson equation and cavity flow problem, we confirmed the possibility of computational acceleration with fuzzy logic and qualitative reasoning in numerical simulations. Numerical experiments with the fuzzy controller resulted in generating a good performance.

• Journal of Industrial Technology
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• v.15
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• pp.195-202
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• 1995

In this paper, we analyze the effects of scaling factors on the performance of a fuzzy controller. The quantitative relation between input and output variables of a fuzzy controller is obtained by using a quasi-linear fuzzy model. And an approximate transfer function of a fuzzy controller is derived from the comparison of fuzzy controller with the conventional PID controller. Then we analyze the effects of scaling factor using this approximate transfer function and root locus method.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.5
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• pp.819-826
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• 1994

This paper deals with a self-tuning fuzzy controller. The fuzzy controller is constructed with linguistic rules which consist of the fuzzy sets. Each fuzzy set is characterized by a membership function. The tuning fuzzy controller has paramenters that are input/output scaling factors to effect control output. In this paper we propose a tuning method for the scaling factor Computer simulations carried out on first-order and second-order processes will show how the present tuning approach improves the transient and the steady-state characteristics of the overall system.The applicability of the proposed algorithm is certified by computer simulation results.