• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.05a
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• pp.144-147
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• 2001

This paper presents adaptive fuzzy controller which is uncertainty or unknown variation in different parameters with nonlinear system of helicopter. The proposed adaptive fuzzy controller applied TSK(Takagi-Sugeno-Kang) fuzzy system which is not only low number of fuzzy rule, and a linear input-output equation with a constant term, but also can represent a large class of nonlinear system with good accuracy. The adaptive law was designed by using Lyapunov stability theory. The adaptive fuzzy controller is a model reference adaptive controller which can adjust the parameter $\theta$ so that the plant output tracks the reference model output. First of all, system of helicopter was considered as stopping state, and design of controller was simulated from dynamics equation with stopping state. Results show that it is controlled more successfully with a model reference adaptive controller than with a non-adaptive fuzzy controller when there is a modelling error between system and model or a continuous added noise in such unstable system.

• Honam Mathematical Journal
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• v.39 no.4
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• pp.527-559
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• 2017

The main motivation of this article is to generalized the concept of fuzzy ideals, (${\alpha},{\beta}$)-fuzzy ideals, (${\in},{\in}{\vee}q_k$)-fuzzy ideals of semigroups. By using the concept of $q^{\delta}_K$-quasi-coincident of a fuzzy point with a fuzzy set, we introduce the notions of (${\in},{\in}{\vee}q^{\delta}_k$)-fuzzy left ideal, (${\in},{\in}{\vee}q^{\delta}_k$)-fuzzy right ideal of a semigroup. Special sets, so called $Q^{\delta}_k$-set and $[{\lambda}^{\delta}_k]_t$-set, condition for the $Q^{\delta}_k$-set and $[{\lambda}^{\delta}_k]_t$-set-set to be left (resp. right) ideals are considered. We finally characterize different classes of semigroups (regular, left weakly regular, right weakly regular) in term of (${\in},{\in}{\vee}q^{\delta}_k$)-fuzzy left ideal, (${\in},{\in}{\vee}q^{\delta}_k$)-fuzzy right ideal and (${\in},{\in}{\vee}q^{\delta}_k$)-fuzzy ideal of semigroup S.

• Journal of the Korean Society of Safety
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• v.15 no.4
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• pp.69-77
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• 2000

This paper presents a study for decision method of human body safety according to power load fluctuation of the Chechon area. To cope with substantial electromagnetics analysis, the safety assessments were analyzed the double 154 [kV] T/L, 345 [kV] T/L, Chechon-Ichon, Chechon-Youngju, respectively. As the results of case study, in case of 345 [kV] T/L, the electric field value was 11.4927 [kV/m], magnetic field value was 0.4622 [G] at the point about 7 [m] away from the line in severest case. The results showed that the membership of a proposition fuzzy '11.4937 [kV/m] is hazardous' is 0.7063 for the severest case in case of 345 [kV] T/L. As the analytic results using the fuzzy qualifier term, the membership in case of very false is 0.0862 and fairly false is 0.5419, respectively.

• Journal of Energy Engineering
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• v.6 no.1
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• pp.19-25
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• 1997

This paper presents the short-term operation scheduling on cogeneration system connected with auxiliary equipment by using the possibility fuzzy theory. The possibility fuzzy theory is a method to obtain the possibility boundary of the solution from the fuzzification of coefficients. Simulation is carried out to obtain the boundary of heat production in each time interval. Simulation results show the flexible operation boundary to establish effectively operation scheduling.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.491-493
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• 1995

In this paper, the method of long-term load forecasting using a fuzzy neural network of which input is a fuzzy membership function value of a input variable like as GNP which is considered to affect demand of load. The proposed method was applicated in Korea Electric Power Corporation (KEPCO). The comparison with Error Back-Propagation Neural Network has been shown.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.2
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• pp.108-112
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• 2012

A sustainable production of electricity is essential for low carbon green growth in South Korea. The generation of wind power as renewable energy has been rapidly growing around the world. Undoubtedly wind energy is unlimited in potential. However, due to its own intermittency and volatility, there are difficulties in the effective harvesting of wind energy and the integration of wind power into the current electric power grid. To cope with this, many works have been done for wind speed and power forecasting. It is reported that, compared with physical persistent models, statistical techniques and computational methods are more useful for short-term forecasting of wind power. Among them, support vector regression (SVR) has much attention in the literature. This paper proposes an SVR based wind speed forecasting. To improve the forecasting accuracy, a fuzzy clustering is adopted in the process of SVR modeling. An illustrative example is also given by using real-world wind farm dataset. According to the experimental results, it is shown that the proposed method provides better forecasts of wind power.

• Journal of Navigation and Port Research
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• v.26 no.2
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• pp.193-197
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• 2002

This paper suggests a method to design TSK(Takagi-Sugeno-Kang) fuzzy nonlinear control system for automatic steering system which contains the nonlinear component of ship's maneuvering equation. A TSk fuzzy model can be identified using input-output data and represent a nonlinear system very well. A TSK fuzzy controller can be designed systematically from a TSK fuzzy model because the consequent part of TSK fuzzy rule is a linear input-output equation having a constant term. Therefore, this paper suggests the method identifying the TSK fuzzy model and designing the TSK fuzzy controller based on the TSK fuzzy model for ship steering.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.6
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• pp.1041-1045
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• 2010

Short-term electric load forecasting of power systems is essential for the power system stability and the efficient power system operation. An accurate load forecasting scheme improves the power system security and saves some economic losses in power system operations. Due to scarcity of the historical same type of holiday load data, most big electric load forecasting errors occur on load forecasting for the holidays. The fuzzy linear regression model has showed good accuracy for the load forecasting of the holidays. However, it is not good enough to forecast the load of the election day. The concept of the load variation rate for the load forecasting of the election day is introduced. The proposed algorithm shows its good accuracy in that the average percentage error for the short-term 24 hourly loads forecasting of the election days is 2.27%. The accuracy of the proposed 24 hourly loads forecasting of the election days is compared with the fuzzy linear regression method. The proposed method gives much better forecasting accuracy with overall average error of 2.27%, which improved about average error of 2% as compared to the fuzzy linear regression method.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1289-1294
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• 2003

This paper proposes a novel and efficient intelligent digital redesign technique for a Takagi-Sugeno (TS) fuzzy system. The term of intelligent digital redesign involves converting an existing analog fuzzy-model-based controller into an equivalent digital counterpart in the sense of state matching. In this paper, we suggest the discretization method based on the dual-rate sampling approximation is first proposed, and then attempt to globally match the states of the overall closed-loop TS fuzzy system with the pre-designed analog fuzzy-model-based controller and those with the digitally redesigned fuzzy-model-based controller. To show the feasibility and the effectiveness of the proposed method, a computer simulation is provided.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09b
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• pp.129-132
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• 2003

This paper proposes a novel and efficient intelligent digital redesign technique for a Takagi-Sugeno (TS) fuzzy system. The term of intelligent digital redesign involves converting an existing analog fuzzy-model-based controller into an equivalent digital counterpart in the sense of state matching. In this paper, we suggest the discretization method based on the dual-rate sampling approximation is first proposed, and then attempt to globally match the states of the overall closed-loop TS fuzzy system with the pre-designed analog fuzzy-model-based controller and those with the digitally redesigned fuzzy-model-based controller. To show the feasibility and the effectiveness of the proposed method, a computer simulation is provided.