• Proceedings of the Safety Management and Science Conference
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• 2003.11a
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• pp.185-198
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• 2003

This study is to develop and operate the R-FCE(Real-time Fuzzy Control Expert System) model on the SBR(Sequency Batch Reactors) type sewage disposal facility which is for the environmental problem of future and the effective treatment. It is the system that regularly handles the input, output information in real time by the Fuzzy control IF-THEN rule. Nowadays the water pollution caused by the increase of population and the industrialization already exceeds the purifying ability of nature and is getting worse. The sewage disposal facility needs an expert having wide experience and know-how because the quality or quantity of inflow water is so irregular that the process of sewage disposal is difficult. In the nation, however, the accumulation of technology is so weak because field-operators avoid the long-term duty. So the accurate and speedy decision or control of field are difficult in the case of emergency situation.

• Nuclear Engineering and Technology
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• v.25 no.3
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• pp.371-380
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• 1993

A model free controller utilizing a set of linguistic fuzzy logic of the human operator's experience is developed to control the steam generator water level in a pressurized water reactor. Only 9 rules for control action are generated from the inputs of water level error and mass flow error implicitly representing the time variation of the collapsed water level. The bell type membership functions of the premise side and the result side are tuned by the sensitivity study. This compact fuzzy logic controller shows a robust control during transient and no offset error and oscillation during steady state operation. For a multi-ramp power increase from start-up to full power, the proposed controller shows good performance for the entire range.

• Journal of the Society of Naval Architects of Korea
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• v.45 no.2
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• pp.213-220
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• 2008

The aim of this paper is to build up the design model using ASMOD(Adaptive Spline Modeling of Observation Data) for the optimum scale of fleet, ship particulars and ship speed, etc. ASMOD, which define membership functions of fuzzy rule as B-spline basis function, represents a whole system as the sum of the sub-model. As it reduces the number of division of the space generated by the fuzzy set of input variables, it has a advantage of simplification to model structure and is efficient to represent the non-linear model.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2292-2295
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• 2001

In this paper, The control problem for a series DC motor is considered to adaptive fuzzy sliding-mode control scheme. Based on a nonlinear mathematical model of a series connected DC motor, instead of the combination of a nonlinear transformation and state feedback(feedback linearization) reduces the nonlinear control design. To demonstrate its effectiveness, an experimental study of this controller is presented. Two sets of fuzzy rule bases are utilized to represent the equivalent control input with unknown system functions of the main target. The membership functions of the THEN-part, which is used to construct a suitable equivalent control of SMC, are changed according to the adaptive law. With such a design scheme, we not only maintain the distribution of membership functions over state space but also reduce computing time considerably.

• Proceedings of the KIEE Conference
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• 2005.10c
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• pp.114-117
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• 2005

Auto Steering System is the device for course keeping or course altering to ship's steering system. The Purpose of automatic steering system is to keep the ship's course stable with the minimum course and rudder angle. Recently, modern control theories are being used widely in analyzing and designing the ship system. Though P.D type auto pilots are widely used in ships, the stability and the adjusting methods are not clarified. In this paper the authors proposed auto steering system with Fuzzy Logic Controller. In the fuzzy control the things that the actual operators of a steering wheel has acquired through their experience can be logically described by the Lingustic Control Rule. The characteristic of the control system were investigated through the computer simulation results. it was found that the fuzzy logic control was more efficient than the conventional system.

• Journal of Advanced Marine Engineering and Technology
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• v.20 no.3
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• pp.137-143
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• 1996

The propulsion marine diesel engine has been widely applied with a mechanical-hydraulic governor to control the ship speed for long time. But it was recently very difficult for the mechanical-hydraullic governor to control the speed of engine under the condition of low speed and low load because of jiggling and hunting by rough fluctuation of rotating torque. To solve these problems of control systems, the performance improvement of mechanical-hydraulic governor is required. In this paper, in order to analyze the speed stability of control systems, the influence of parameters of the engine dead time, gain, damping ratio was discussed on the view of control engineering. The performance improvement of a conventional mechanical hydraulic governor is confirmed to be possible by fuzzy control scheme.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.11
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• pp.2108-2116
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• 2008

The paper concerns Fuzzy C-Means clustering based Radial Basis Function neural networks (FCM-RBFNN) and the optimization of the network is carried out by means of Particle Swarm Optimization(PSO). FCM-RBFNN is the extended architecture of Radial Basis Function Neural Network(RBFNN). In the proposed network, the membership functions of the premise part of fuzzy rules do not assume any explicit functional forms such as Gaussian, ellipsoidal, triangular, etc., so its resulting fitness values directly rely on the computation of the relevant distance between data points by means of FCM. Also, as the consequent part of fuzzy rules extracted by the FCM - RBFNN model, the order of four types of polynomials can be considered such as constant, linear, quadratic and modified quadratic. Weighted Least Square Estimator(WLSE) are used to estimates the coefficients of polynomial. Since the performance of FCM-RBFNN is affected by some parameters of FCM-RBFNN such as a specific subset of input variables, fuzzification coefficient of FCM, the number of rules and the order of polynomials of consequent part of fuzzy rule, we need the structural as well as parametric optimization of the network. In this study, the PSO is exploited to carry out the structural as well as parametric optimization of FCM-RBFNN. Moreover The proposed model is demonstrated with the use of numerical example and gas furnace data set.

• Journal of Biosystems Engineering
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• v.23 no.4
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• pp.365-372
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• 1998

This study was carried out to develop a nutrient-solution mixing-and-supplying system, which used a low-cost metering device instead of expensive metering pumps and a fuzzy logic controller. A low cost and precise overflow-type metering device was developed and evaluated by testing the flow discharge for the automatic nutrient-solution mixing-and-supplying system for snail-scale hydroponic sewers. The fuzzy logic controllers, which could predict and meet the desired values of EC and supply rate of nutrient solution were developed and verified by simulation and experiment. this fuzzy logic controller, whose algorithm consists of four crisp inputs, two crisp outputs and nine rules, was developed to predict the desired value of EC and supply rate of nutrient solution and two crisp inputs, one crisp output and nine rules used to control EC to the desired values. The nutrient-solution mixing-and-supplying system showed satisfactory EC control performance with the maximum overshooting of 0.035 mS/cm and the maximum settling time of 15 minutes in case of increasing 0.7 mS/cm. also, the accuracy of the overflow-type metering device in terms of the full-scale error was 2.29% when using solenoid valve only and 0.2% when using solenoid valve and flow control valve together.

• Proceedings of the KIEE Conference
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• 1997.11a
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• pp.505-508
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• 1997

In this paper, an auto-tuning method for fuzzy controller based on the neural network is presented. The backpropagated error of neural emulator offers the path which reforms the fuzzy controller's membership functions and fuzzy rule, and used for speed control of induction motor. For the torque control method, an indirect vector control scheme with slip calculation is used because of its stable characteristics regardless of speed. Motor input current is regulated by a current controlled voltage source PWM inverter using space voltage vector technique. Also, the scheme of current control fuzzy controller is synchronous reference frame with decoupling term. DSP(TMS320C31) is used to achieve the high speed calculation of the space voltage vector PWM and to build the self-learning fuzz. control algorithm. An IPM is used to simplify hardware design.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.11
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• pp.103-110
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• 1990

This paper studies on an on-line recognition of handwritten Hangeul characters using the fuzzy inference. To solve the ambiguity due to the variations of writing style by writes, these handwri-tten characters are recognized by means of the fuzzy inference on the production rule which is generated with every relative position information between strokes. In order to reduce the processing time, a subgroup which is previously classified with the number of strokes of reference characters is selected according to the number of strokes of input character, and the tolerance limit of distances between input character and reference characters of a subgroup is introduced to reduce the reference characters which is applied to the fuzzy inference. Experimental results for handwritten Hanguel charters 3990 by 10 writers show the recognition rate of $99.5{\%}$and the average processing time of 0.4sec/character.