• Proceedings of the Acoustical Society of Korea Conference
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• spring
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• pp.325-328
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• 2004

본 논문에서는 PAST(Projection Approximation Subspace Tracking)에 기반 한 새로운 부공간(subspace) 추적 알고리즘을 제안하고자 한다. 빠른 시분할 대상의 목표물의 방위각을 추정하는 것이 필요하다. 그러나 PAST 기법은 고속의 시분할 환경에서는 잘 동작하지 않는다 따라서 가변망각 인자를 도입하여 빠르게 변화하는 부공간의 비정재 (Nonstationary) 상태에 잘 적응시켜 PAST 성능 향상을 보고자 한다.

• Proceedings of the KIPE Conference
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• 2000.07a
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• pp.199-202
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• 2000

The accurate identification of the motor parameters in crucially important to achieve high dynamic performance of induction motors. In this paper parameter auto-tuning algorithms for stator(rotor) resistance stator(rotor) leakage inductance mutual inductance and rotor inertia. Stator(rotor) resistance and stator(rotor) leakage inductance are identified based on the stationary coordinate and mutual inductance and rotor resistor on the scalar speed control and the transient motor terminal voltage. To demonstrate the practical significance of our results we present some experimented results.

• Proceedings of the KAIS Fall Conference
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• 2007.05a
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• pp.147-149
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• 2007

"Dynamic Neural Unit"(DNU) based upon the topology of a reverberating circuit in a neuronal pool of the central nervous system. In this thesis, we present a genetic DNU-control scheme for unknown nonlinear systems. Our methodis different from those using supervised learning algorithms, such as the backpropagation (BP) algorithm, that needs training information in each step. The contributions of this thesis are the new approach to constructing neural network architecture and its trainin.

• Proceedings of the KIPE Conference
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• 1998.11a
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• pp.1-4
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• 1998

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 switched reluctance motor. The experiments are performed to verify the capability of proposed control method on 6/4 salient type SRM. The results show that fuzzy-neural controller is suitable for wide speed range.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.128.3-128
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• 2001

In this paper we proposed that the speed of induction motor is controlled by a PI controller, which could control unknown motor using Neural Network for auto-tuning of the PI parameter. The parameters of the PI controller were adjusted to reduce the speed error of the controlled motor. The input parameters of the Neural Network controller are the speed, q-axis current, and speed reference of the induction motor respectively. The usefulness of proposed controller will be confirmed by simulation which we compare with conventional PI controller.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.413-417
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• 1989

The idea of expert control is to incorporate a rule based expert system in a feedback control system. In this paper, the expert system concepts are instead used as an element of the feedback loop in a single controller. The algorithms are coded in as pure form as possible and the heuristic logic is implemented as rules. This paper reports on effort to produce an implementation of an expert controller on microcomputer based system, including an industrial programmable controller.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.113-116
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• 1990

In this paper, An expert system for electric furnace with time delay is proposed. The expert system uses Fuzzy control theory. The conventional controller uses Auto-Tuning control theory. From experiment, we can obtain that the response of expert system is superior to the response of the conventional controller. In this experiment, the expert controller is implemented with the IBM PC. The 8751 One chip processor controling the electric furnace is used.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.110-113
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• 2002

This paper propose a method for the temperature control using cool-plate in the track equipment. The employed control algorithm is PID control algorithm. The control gains are found using relay auto-tuning algorithm. After that the gains are adjusted manually in trial and error. The control hardware circuit is designed and implemented in the lab. The controlled temperature reached the desired value Within $\pm0.05^{\circ}C$ accuracy.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.4
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• pp.39-46
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• 2009

• Proceedings of the KIEE Conference
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• 1997.07b
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• pp.732-734
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• 1997

This paper describes the design and implementation of a fuzzy temperature control system to control the water temperature in plant. For evaluating the performance of a fuzzy controller, the experiment results of a fuzzy controller are compared with these of a conventional PID controller which provides an auto-tuning function. The experiment results show that the proposed controller has a good control performance and is robust to external disturbance.