• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.11 no.2
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• pp.102-109
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• 1997

The width of fuzzy membership function and control rule has an effect on performance of the fuzzy controller for electric equipment systems. In this paper, the neuro-fuzzy controller is proposed to im¬prove the performance of fuzzy controller. It has the width of membership function, that is adapted to the electrical parameter using multi-layer neural network, it is applied to first order electric power system with dead time and various plant constant. The related simulation resolts show that the pro¬posed neuro fuzzy controller are superior characteristics of improved performance

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.1923-1924
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• 2006

본 논문은 HVAC(heating, ventilating, and air conditioning) 시스템에 대하여 Multi Fuzzy 제어기 설계를 제안한다. HVAC 시스템은 Compressor(압축기), Condenser(응축기), Evaporator(증발기), Expansion Valve 로 구성되며, 각각의 기기에 대한 제어가 독립적으로 이루여져 있다. 기존의 제어가 한 제어기를 사용한 단일방식으로 이루어지다보니 HVAC 시스템의 특성인 냉매의 상태가 달라지면 시스템 전반적으로 그 영향이 파급되는 부분까지 고려를 해 주지 못하고, 제어기의 성능이 효율적이지 못했다. 본 논문에서는 비선형성이 강하고 불확실하며 복잡한 시스템을 쉽게 제어할 수 있는 Fuzzy 제어기를 구성하여 Expansion Valve 와 Compressor 에서 동시에 제어하는 Multi 제어기를 설계한다. 제안된 Multi Fuzzy 제어기는 HVAC 시스템의 효율성과 안정성에 기초하여, 과열도와 저압을 제어한다.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.40 no.3
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• pp.199-207
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• 2003

This paper is proposed new fuzzy controller for high performance of interior permanent magnet synchronous motor(IPMSM) drive. New fuzzy controller take out appropriate amounts of accumulated control input according to fuzzily described situations in addition to the incremental control input calculated by conventional direct fuzzy controller The structures of the proposed controller is motivated by the problems of direct fuzzy controller. The direct controller generally give inevitable overshoot when one tries to reduce rise time of response especially when a system of order higher than one is under consideration. The undesirable characteristics of the direct fuzzy controller are caused by integrating operation of the controller, even though the Integrator itself is introduced to overcome steady state error in response. Proposed controller fuzzily clear out integrated quantities acrording to situation. This paper attempts to provide a thorough comparative insight into the behavior of IPMSM drive with direct and new fuzzy speed controller. The validity of new fuzzy speed controller is confirmed by response results for IPMSM drive system.

• Transactions of the Korean Society of Mechanical Engineers
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• v.16 no.7
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• pp.1234-1243
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• 1992

A systematic procedure to design fuzzy PID controllers is developed in this paper. The concept of local fuzzy control cell is proposed by introducing both an adequate global control rule and membership functions to simplify a fuzzy logic controller. Fuzzy decision is made by using algebraic product and parallel firing arithematic mean, and a defuzzification strategy is adopted for improving the computational efficiency based on nonfuzzy micro-processor. A direct method, transforming the typical output of quasi-linear fuzzy operator to the digital compensator of PID form, is also proposed. Finally, the proposed algorithm is applied to an DC-servo motor. It is found that this algorithm is systematic and robust through computer simulations and implementation of controller using Intel 8097 micro-processor.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.1
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• pp.122-129
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• 2008

The direct torque control method of an inverter fed squirrel cage typed induction motor using fuzzy logic controller has been proposed. This method is suitable for the traction which requires a fast torque response during the star-up and step change. The fuzzy control algorithm based upon the control principles of conventional DSC(Direct Self Controller) is developed. The fuzzy algorithm is tarried out by defuzzification strategy of the fuzzy output extracted from the possibility distribution of an inferred fuzzy control rule. The flux and torque of an induction motor are estimated by the dynamic model of the rotor flux field-oriented scheme which has decoupling characteristics and excellent dynamic response over a wide speed range. The proposed controller shows a good dynamic response. Moreover, since the fuzzy controller possesses highly adaptive capability, the performance of fuzzy controller is quite robust and insensitive to the motor parameters and change of operation conditions.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.2 no.4
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• pp.29-36
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• 2009

The fuzzy controller of the FFH(Fuel Fired Heater) used for vehicle is designed in this study. Two of the most important things of the pre-heater are how fast it can be at the set temperature and how to reduce the temperature deviation in the space to a minimum. The temperature deviation of the existed FFH with PI controller for temperature controller was reduced. Also, the fuzzy controller improved the response characteristics, and then the performance was inspected. When setting the temperature in this designed fuzzy controller, it took 12 minutes in the existed PI control method to reach $25^{\circ}C$. However, it took 9 minutes and 20 seconds in the fuzzy control method. Therefore, it is proved that the fuzzy controller is better than the existed one with fast response performance as 2 minutes 40 seconds. The temperature deviation was $2.4^{\circ}C$ in the existed control method but $1.6^{\circ}C$ in the designed fuzzy controller. Accordingly, the temperature deviation was improved too.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.181-183
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• 1996

Generally, While position type fuzzy controller has good performance in transient period, it has uniform steady state error of response. While velocity type fuzzy controller is capable of reducing steady state error of response, it is hard to develop the performance in transient period. In order to have both good performance in transient period and ability to reduce the steady state error of response, weighting fuzzy controller, which is composed of these two fuzzy controllers, is proposed. For the decision of weight to each fuzzy controller, Weighting fuzzy set is established according to the system state variables and applied to each fuzzy controller. The proposed weighted fuzzy controller has the merits of both position type fuzzy controller and velocity type fuzzy controller simultaneously.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.1
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• pp.120-125
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• 2005

In this paper, We propose the fuzzy controller for the gain tuning of PID controller The proposed controller doesn't use the crisp output error and rule tables though with a fuzzy inference process in forward fuzzifier, New Fuzzy PID Controller assigns relations and ranges of two variables of PID gain parameters. These new gain parameters are calculated by the fuzzy inference with max-min ranges of Kp and Kd. The Ki parameter is computed automatically between Kp and Kd parameter Is calculated by Ziegler-Nickels tuning rules. Finally we experimented the propose controller by the hydraulic servo motor control system. We can obtained desired results through the good control characteristics.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.1
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• pp.112-117
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• 2004

This paper suggests the design and analysis of the fuzzy sliding mode control for a nonlinear system using Takagi-Sugeno(T-S) fuzzy model. In this control scheme, identifying procedure that the input gain matrices in a T-S fuzzy model are manipulated into the same one is needed. The input disturbances generated in the identifying procedure are resolved by incorporating the disturbance treatment method of the conventional sliding mode control. The proposed control strategy can also treat the input disturbances that can not be linearized in the linearization procedure of T-S fuzzy modeling. Design example for the nonlinear system, an inverted pendulum on a cart, demonstrates the utility and validity of the proposed control scheme.

• Journal of the Institute of Convergence Signal Processing
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• v.3 no.4
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• pp.42-48
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• 2002

The case that cannot show the satisfactory control results with a modeling error and a shortage of related knowledge about a plant is if a fuzzy controller designed based on the plant model or the experience applies to an actual plant. We must adjust the scale factor which is a controller again in order to improve control performance in case of this and needs a lot of time and costs because this regulation process is carried out with a trial and error way We proposes the fuzzy controller that an automatic control adjust scale factors according to fuzzy logic and normalizer in this paper We confirmed that an automatic adjusted fuzzy controller displayed good performance than the fuzzy controller that scale factors was fixed through simulation. We implemented the controller using the DSP processor and applied in a hydraulic servo system. And then we observed an experimental results.