• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.1
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• pp.33-38
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• 2006

In this paper, we propose a new architecture of Fuzzy Polynomial Neural Networks(FPNN) by means of genetically optimized Fuzzy Polynomial Neuron(FPN) and discuss its comprehensive design methodology involving mechanisms of genetic optimization, especially Genetic Algorithms(GAs). The conventional FPNN developed so far are based on mechanisms of self-organization and evolutionary optimization. The design of the network exploits the extended Group Method of Data Handling(GMDH) with some essential parameters of the network being provided by the designer and kept fixed throughout the overall development process. This restriction may hamper a possibility of producing an optimal architecture of the model. The proposed FPNN gives rise to a structurally optimized network and comes with a substantial level of flexibility in comparison to the one we encounter in conventional FPNNs. It is shown that the proposed advanced genetic algorithms based Fuzzy Polynomial Neural Networks is more useful and effective than the existing models for nonlinear process. We experimented with Medical Imaging System(MIS) dataset to evaluate the performance of the proposed model.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.15 no.2
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• pp.131-138
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• 2016

In order to improve the performance of an extended Kalman filter, a simplified indirect inference method (SIIM) fuzzy logic system (FLS) is proposed. The proposed FLS is composed of two fuzzy input variables, four fuzzy rules and one fuzzy output. Two normalized fuzzy input variables are the variance between the trace of a prior and a posterior covariance matrix, and the residual error of a Kalman algorithm. One fuzzy output variable is the weighting factor to adjust for the Kalman gain. There is no need to decide the number and the membership function of input variables, because we employ the normalized monotone increasing/decreasing function. The single parameter to be determined is the magnitude of a universe of discourse in the output variable. The structure of the proposed FLS is simple and easy to apply to various nonlinear state estimation problems. The simulation results show that the proposed FLS has strong adaptability to estimate the states of the incoming/outgoing moving objects, and outperforms the conventional extended Kalman filter algorithm by providing solutions that are more accurate.

• Proceedings of the KIPE Conference
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• 2001.12a
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• pp.11-14
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• 2001

Direct torque control (DTC) scheme provides a very quick torque response without the complex field-orientation block and inner current regulation loop. DTC is known as an appropriate scheme for high power induction motor drives because it can be used at lower switching frequency There are a major drawbacks with the application of DTC schemes it is large current harmonics due to flux drooping in a low speed range. In order to solve the problem, the fuzzy variable switching sector scheme are adopted in this paper. A meaningful contribution of this paper is to propose a simple realization scheme of the fuzzy variable switching sector technique. Experimental results show the effectiveness of this proposition.

• The Transactions of the Korean Institute of Power Electronics
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• v.17 no.3
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• pp.205-212
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• 2012

This paper proposes the fuzzy logic based variable step-size MPPT (Maximum Power Point Tracking) method for the stability at the steady state and the improvement of the transient response in the wind power system. If the change value of duty ratio is set on stability of the steady state, MPPT control traces to maximum power point slowly. And if the change value is set on improvement of the transient response, the system output oscillates at the maximum power point. By adjusting the step size with fuzzy logic, it can be improved the MPPT response speed and stability at steady state when MPPT control is performed to track the maximum power point. The effectiveness of the proposed method has been verified by simulations and experimental results.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.382-386
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• 1992

In this paper, the author proposed FLVSC(Fuzzy Logic Variable Structure Controller), of which control rules are extracted from the concepts of VSC(Variable Structure Control). FLC(Fuzzy Logic Controller) based on linguistic rules has the advantages of not needing of some exact mathematical model for plant to be controlled. The proposed method has the characteristics which are viewed in conventional VSC, e.g. insensitivity to a class of disturbances, parameter variations and uncertainties in sliding mode. In addition, the method has the properties of FLC - noise rejection capability etc. The computer simulations have been carried out for a DC servo motor to show the usefulness of the proposed method and the effects of disturbances and parameter variations are considered.

• Proceedings of the KIPE Conference
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• 1998.07a
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• pp.361-365
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• 1998

In this paper, the sliding mode variable structure-fuzzy(SMVS-F) control algorithm is applied to speed controller for field oriented induction motor drive system. According to the principle of sliding mode variable structure-fuzzy adjustable speed control scheme, the proposed algorithm shows good performances which are reducing chattering, robustness against parameter variation in induction motor drive. The validity of the proposed control scheme is verified by computer simulation using SIMULINK.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.5
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• pp.809-818
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• 1994

In this paper , the author proposed FLVSC (Fuzzy Logic Variable Structure Controller),of which control rules are extracted from the concepts of VSC(Variable Structure Control). FLC(Fuzzy Logic Controller) based on linguistic rules has the advantages of not needing of some exact mathematical model for plant to be controlled. The proposed method has the characteristics which are viewed in conventional VSC, e.g. insensitivity to a class of disturbances, parameter variations and uncertainties in sliding mode. In addition, the method has the properties of FLC-noise rejection capability etc. The computer simulations have been carried out for position control of DC servo motor to show the usefulness of the proposed method and the effects of disturbances and parameter variations are considered.

• Journal of the Korean Society of Safety
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• v.12 no.2
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• pp.70-79
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• 1997

This paper presents a study on the fuzzy linguistic variable based approach for safety assessment of human body in ELF electromagnetic field considering power system states. To cope with the demand in modern industry, the power system becomes larger in scale, higher in voltage. The advent of high voltage system has increased the relative importance of field effects. The analysis of ELF electromagnetic field based on Quasi-Static Method is introduced while the power system is included to model the expected and/or unexpected uncertainty caused by the load fluctuation and parameter changes. In order to analyze the power system, Monte Carlo simulation method and contingency analysis method are adopted in normal state and alert state, respectively. In the safety assessment of human body, the approach based on fuzzy linguistic variable is employed to overcome the shortcomings resulting from a crisp set concept. The suggested scheme is applied to a sample system(modified IEEE 14 bus system) to validate the usefulness.

• Communications for Statistical Applications and Methods
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• v.15 no.6
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• pp.799-813
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• 2008

This paper deals with the properties of the fuzzy least squares estimators for fuzzy linear regression model. Especially fuzzy triangular input-output model including error term is proposed. The error term is considered as a fuzzy random variable. The asymptotic unbiasedness and the consistency of the estimators are proved using a suitable metric.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.394-397
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• 2004

In this paper, we consider interval number-valued random variables and fuzzy number-valued random variables and discuss Choquet integrals of them. Using these properties, we define the Choquet expected value of fuzzy number-valued random variables which is a natural generalization of the Lebesgue expected value of Lebesgue expected value of fuzzy random variables. Furthermore, we discuss some application of them.