• Proceedings of the KIPE Conference
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• 2004.07a
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• pp.38-41
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• 2004

Artificial intelligence control that use Fuzzy, Neural network, genetic algorithm etc. in the speed control of induction motor recently is studied much. Also, sensors such as Encoder and Resolver are used to receive the speed of induction motor and information of position. However, this control method or sensor use receives much effects in surroundings environment change and react sensitively to parameter change of electric motor and control Performance drops. Presume the speed and position of induction motor by ANN in this treatise, and because using FMRLC that is consisted of two Fuzzy Logic, can correct Fuzzy Rule Base through teaming and save good response special quality in change of condition such as change of parameter.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.20 no.1
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• pp.86-93
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• 2012

Fuzzy control has emerged as a practical alternative to classical control schemes in controlling certain time-varying, nonlinear, and ill-defined processes. As the current of this kind of a research paradigm, we concluded that there is a need for application study of a fuzzy control theory to the flight control systems of small aircraft being to be developed at KARI. And then, this preliminary study was carried out to the automatic landing system of the canard aircraft (Firefly) for the purpose of the preparation of extension of research contents and various application areas, in which FMRLC was chosen as the fuzzy controller of the system.

• Journal of Mechanical Science and Technology
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• v.18 no.1
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• pp.1-11
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• 2004

The ionic Polymer Metal Composite (IPMC) is one of the electroactive polymers (EAP) that was shown to have potential application as an actuator It bends by applying a low voltage current (1∼3 V) to its surfaces when containing water In this paper, the basic characteristics and the static ＆ dynamic modeling of IPMC is discussed. In modeling and analysis, the equations of motion, which describe the total dynamics of the system, are driven. To control the position of the IPMC actuator, an adaptive fuzzy algorithm is used. IPMC is a time varying system because the some parameters vary with the passage of time. In this paper, the modeling and control of IPMC is introduced.