• Transactions of The Korea Fluid Power Systems Society
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• v.4 no.2
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• pp.28-33
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• 2007

In the power plant facility which use soft coal as a power source the fan pitch blade control hydraulic actuator is used to control the inlet and outlet gas to regulate the internal pressure of the furnace and control the frequence. Sometimes malfunctions of this equipment lead to the decline of boiler thermal efficiency and unexpected power plant trip. In order to localize the fan pitch blade control hydraulic actuator specially for the 500MW large scale boiler, Analysis and modelling of the system is carried out mathematically. The responses of the system are examined by using matlab simulation fur the variation of the major parameters in view of reverse engineering. Consequently the validity of the established parameters are examined.

• Journal of Satellite, Information and Communications
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• v.8 no.1
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• pp.61-65
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• 2013

In this paper, we propose system model to solve conventional threshold problem of using fixed false alarm for energy spectrum sensing. Spectrum sensing reliability is ensured when Secondary user have high SNR. Thus, it is not reasonable using fixed optional false alarm without considering CR user's SNR. So, we propose adaptive threshold method. adaptive threshold is decided by controling FA according to CR user's SNR.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.29 no.4
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• pp.286-291
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• 1993

This paper presents a design method of fuzzy controller based on TSK fuzzy model. By using the proposed method, we can design fuzzy controller mathematically, which guarantees the stability of fuzzy system. We derived a theorem related to the stability of fuzzy system. In that theorem, we show that the fuzzy system has the same stable state transition matrix as we desire. The validity of the proposed method is shown through an experiment of DC motor velocity control.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.2
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• pp.90-96
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• 2005

This paper presents hardware scheme of fuzzy inference engine, based on α-level set decomposition of fuzzy sets for fuzzy control of DC servo system. We propose a method which is directly converted to PWM actuating signal by a one body of fuzzy inference and defuzzification. The influence of quantity α-levels on input/output characteristics of fuzzy controller and output response of DC servo system is investigated. It is concluded that quantity α-cut 4 give a sufficient result for fuzzy control performance of DC servo system. The experimental results shows that the proposed hardware method is effective for practical applications of DC servo system.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.12
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• pp.663-670
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• 2003

This paper deals with speed control of DC servo motor using a Adaptive high gain obserber. In this parer, the gain of the observer is properly set up using the fuzzy control and adaptive high gain observer that have a superior transient characteristic and is easy to implement compared the existing method is designed. In order to verify the performance of the Adaptive high gain observer which is proposed in this paper, it is compared estimate performance of High-gain Observer and Adaptive High Gain Observer with the computer simulation. Effectiveness of the proposed high gain observer is proved from the experiment to compare the case with a speed sensor to the case with Adaptive high gain observer in the speed control of DC servo motor.

• Proceedings of the KIEE Conference
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• 1998.11b
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• pp.423-425
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• 1998

Resonance effects and nonlinear frictions which generate many problems in control system exist in almost all the servo system. therefore, In this paper, the design procedure which employs $H_{\infty}$ control theory after augmenting with two integrators is proposed to track the ramp input. Limit cycles are unavoidable by the effect of interaction between two integrators and Coulomb friction in these system. The describing function is used to check the limit cycles and decide the coefficients of two integrators to minimize the effect of the limit cycles.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.5
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• pp.338-344
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• 2004

This paper presents a sensorless speed control of a DC servo motor using a fuzzy-sliding observer in the presences of load disturbances. A fuzzy-sliding observer is proposed in order to estimate the speed of a motor rotor. First, a sliding observer is used to estimate the derivative of the armature current directly using the armature current mesured in the DC servo motor. Second, the optimal gain of the Luenberger observer is set up using the fuzzy control. Experimental results show the good performance in the DC servo motor system with the proposed fuzzy-sliding observer.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.7
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• pp.428-436
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• 2005

In this paper, we introduce an adaptive control method to improve the position accuracy and reduce nonlinear friction effects for the linear motion servo system with the nonlinear friction. The considered system plant included not only the variation of the mass of mover but also the friction change by the normal force. We also designed an adaptive controller with the mass estimator and the compensator by observing the variation of normal force. The effectiveness and system performances for the proposed control method in this paper show to improve than other control methods through numerical simulations.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.6
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• pp.402-407
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• 2004

This paper proposed a new speed sensorless control method for AC servo motor, which is based on the current observer. Recently, the study in the estimation using a observer is being widely progressed. In order to prove the superiority of the current observer, we made a comparison between the simulation using current observer and that using Luenberger observer. And also, a comparative experiment of the speed control of the AC servo motor using a sensor and using current observer has been executed. The experiment result shows that the estimation using current observer is superior to the estimation using Luenberger observer or to the speed response using a sensor.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.244-247
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• 1993

In this paper, Fuzzy-Neural Network Control system that has the characteristic of fuzzy control to be controlled easily end the good characteristic of a artificial neural network to control the plant due to its learning is presented. A fuzzy rule to be applied is selected automatically by the allocated neurons. The neurons correspond to Fuzzy rules which ere created by a expert. To adaptivity, the more precise modeling is implemented by error beck-propagation learning of adjusting the link-weight of fuzzy membership function in Fuzzy-Neural Network. The more classified fuzzy rule is used to include the property of Dual Mode Method. To test the effectiveness of the algorithm presented above, the simulation for position end velocity of DC servo motor is implemented.