• Journal of the Korean Institute of Intelligent Systems
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• v.27 no.2
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• pp.99-105
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• 2017

Type-2 fuzzy sets are preferred over type-1 sets as they are capable of addressing uncertainty more efficiently. The fuzzifier values play pivotal role in managing these uncertainties; still selecting appropriate value of fuzzifiers has been a tedious task. Generally, based on observation particular value of fuzzifier is chosen from a given range of values. In this paper we have tried to adaptively compute suitable fuzzifier values of interval type-2 possibilistic fuzzy c-means (IT2 PFCM) for a given data. Information is extracted from individual data points using histogram approach and this information is further processed to give us the two fuzzifier values $m_1$, $m_2$. These obtained values are bounded within some upper and lower bounds based on interval type-2 fuzzy sets.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.11
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• pp.167-173
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• 2002

The look up table method conventionally applied to control the inner temperature and humidity of a laver drying machine has repeatedly occurred not only laver's damage but also inferior goods since the reaching time at the optimum state takes a long time. In this paper, a fuzzy control theory instead of the look up table was proposed to reduce the reaching time at the optimum state. The proposed method used six input variables and four output variables for the fuzzy control, and a triangle rule for a fuzzifier, The Mandani's min-max method was applied to a fuzzy inference. Also, the mean method of maximum was applied to a defuzzifier. The method applied to the fuzzy controller contributed to reduce the reaching time at the optimum state, and to minimize not only laver's damage but also inferior goods.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1817-1818
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• 2008

Even though efficiency of coal-fired power plant is proportional to operating temperature, increasement of operating temperature is limited by a technological level of each power plant components. It is an alternative plan to increase operating pressure up to ultra super critical point for efficiency enhancement. It is difficult to control in that pressure within safety guideline that many unexpected phenomena are happen because that region is highly nonlinear region. In this paper, Advanced process control algorithm, ARX and Fuzzifier, is introduced. Then power plant control logics applied Unit Step Optimizer, which is combination of ARX and Fuzzifier are proposed. Its performance is tested and analyzed with design guide line.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1394-1397
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• 1993

A Fuzzy Microprocessor(FMP) is presented, which is suitable for real-time control applications. The features include high speed inference of maximum 114K FLIPS at 20MHz system clocks, capability of up to 128-rule construction, and handing of 8 input variables with 8-bit resolution. In order to realize these features, the fuzzifier circuit and the processing element(PE) are well optimized for LSI implementation. The chip fabricated in 1.2$\mu\textrm{m}$ CMOS technology contains 71K transistors in 82.8 $\textrm{mm}^2$ die size and is packaged in 100-pin plastic QFP.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.12
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• pp.139-148
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• 1995

In this paper an electro-hydraulic servo system is designed by using a fuzzy control algorithm. In order to drive an optimal fuzzy control system, a simulation program for the control system has been developed. By this program the fuzzifier and defuzzifier, a fuzzy inference method, a fuzzy relational matrix, and a fuzzy inference method are investigated. As a result, Larsen inference method, 9*9 fuzzy relational matrix, and center of area defuzzifier are turned out the best as parameters. Finally this method is compared with the conventional PID algotithm, and showed that the fuzzy control performs better than PID algorithm. The fuzzy control performs very well adap- tation against uncertain disturbances.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.520-523
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• 1997

This paper presents FPGA implementation of fuzzy controller using Product-Sum inference method. Product-Sum inference method has much better performance than other inference methods. This fuzzy controller is composed of several digital modules, e.g. fuzzifier, rule base, adder, multiplier, select center and divider, and is operated by error and error variation. We synthesized the fuzzy controller and performed wave simulation using Xilinx VHDL tool(ViewLogic, ViewSim).

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.977.2-980
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• 1993

The fuzzifier circuit DPFC 7 is presented. Its features are: programmable membership function, CMOS digital interface, analog and current mode internal processing and integrability without external components. It has been designed to obtain a basic efficient block for fuzzy processing, to be included in a future architecture.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.2
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• pp.178-183
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• 2004

This paper presents a class of hierarchical fuzzy systems where previous layer outputs are used not in IF-parts, but only in THEN -parts of the fuzzy rules of the current layer. The existence of the proposed hierarchical fuzzy system which approximates a given real continuous function on a compact set is proven if complete fuzzy sets are used in the IF-parts of the fuzzy rules with singleton fuzzifier and center average defuzzifier.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.445-445
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• 2000

This paper proposes the MIMO indirect adaptive fuzzy controller to control the two-link manipulators. The input-output linearization technique, equivalent control input plus integral term, augmented error model and recursive least square adaptive law are used fer the controller. The linear type of fuzzifier-defuzzifier fuzzy logic system used for nonlinear function makes easy to farm the error model and able to follow the adaptive system approach. Such that control approach, the control system is not required joint speed and accerelation measurement and easy to implement and tune. The simulation results showed that the proposed controller has good control performance, stability, very small tracking error, decoupling, fast convergence, robust to parameter variation and load.

• Journal of Power System Engineering
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• v.10 no.4
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• pp.159-164
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• 2006

In recent, the marine engine of a large size is being realized a lower speed, longer stroke and a small number of cylinders for the energy saving. Consequently the variation of rotational torque became larger than former days because of the longer delay-time in fuel oil injection process and an increased output per cylinder. It was necessary that algorithms have enough robustness to suppress the variation of the delay-time and the parameter perturbation. This paper shows the structure of hybrid F-NFC against the delay-time and the perturbation of engine parameter as modeling uncertainties, and the design of the robust speed controller by hybrid F-NFC for the engine. And, The Parameter values of linear equation are determined by RC-GA for F-NFS. The hybrid F-NFC is combined the F-NFC and PID controller for filling up each.