• Proceedings of the KIEE Conference
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• 1996.07a
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• pp.458-460
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• 1996

In this study, the full-state flux observer is designed in the synchronous DQ-frame and the speed adaptation rule is derived by using the MRAS(Model Reference Adaptive System) theory. In this rule, the induction motor becomes a reference model and the flux observer is taken as a adjustable model. A guideline of the adaptation gain is investigated for the precise and stable speed adaptation and the proposed scheme is compared with the conventional one designed in the stationary DQ-frame.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2052-2054
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• 2003

본 논문에서는 혼돈 비선형 시스템의 지능 제어를 위해 간접 적응 제어 기법에 기반한 웨이블릿 신경 회로망 제어기 설계 방법을 제안한다. 제어기 성능에 큰 영향을 미칠 수 있는 웨이블릿 신경 회로망 구조의 파라미터 동정은 본질적으로 강인하고 전역 최적해에 근사한 값을 결정할 수 있는 유전 알고리듬을 사용한다. 본 논문에서 제안한 제어 방법은 유전 알고리듬을 이용한 혼돈 비선형 시스템의 오프라인 동정 모델 및 기준 신호와 플랜트 출력으로 정의되는 제어 오차를 이용하여 원하는 제어 입력을 생성한다. 한편 본 논문에서 제안한 웨이블릿 신경 회로망 제어기를 대표적인 연속 시간 혼돈 비선형 시스템인 Duffing 시스템에 적용하여 설계된 제어기의 효율성 및 우수성을 검증하고자 한다.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.39 no.1
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• pp.51-65
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• 2002

This paper presents a design method of the neural network-based controller using an indirect adaptive control method to deal with an intelligent control for chaotic nonlinear systems. The proposed control method includes the identification and control Process for chaotic nonlinear systems. The identification process for chaotic nonlinear systems is an off-line process which utilizes the serial-parallel structure of multilayer neural networks and simple state space neural networks. The control process is an on-line process which uses the trained neural networks as the system model. An error back-propagation method was used for training of identification and control for chaotic nonlinear systems. The performance of the proposed neural network controller was evaluated by application to the Duffing equation and the Lorenz equation, and the proposed controller was compared with other neural network-based controllers by computer simulations.

• Journal of KSNVE
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• v.10 no.6
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• pp.1059-1066
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• 2000

In this paper. a new indirect feedback active noise control (ANC) scheme barred on the fundamental frequency estimation is proposed for systems with a harmonic noise. When reference signals necessary for feedforward ANC configuration are difficult to obtain, the conventional ANC algorithms for multi-tonal noise do not measure the reference signals but generate them with the estimated frequencies.$^{(4)}$ However, the beating phenomena, in which certain frequency components of the noise vanish intermittently, may make the adaptive frequency estimation difficult. The confusion in the estimated frequencies due to the beating phenomena makes the generated reference signals worthless. The proposed algorithm consists of two parts. The first part is a reference generator using the fundamental frequency estimation and the second one is the conventional feedforward control. We propose the fundamental frequency estimation algorithm using decision rules. which is insensitive to the beating phenomena. In addition, the proposed fundamental frequency estimation algorithm has good tracking capability and lower variance of frequency estimation error than that of the conventional cascade ANF method.$^{(4)}$ We are also able to control all interested modes of the noise, even which cannot be estimated by the conventional frequency estimation method because of the poor S/N ratio. We verify the performance of the proposed ANC method through simulations for the measured cabin noise of a passenger ship and the measured time-varying engine booming noise of a passenger vehicle.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.06a
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• pp.263-268
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• 2000

In this paper, a new indirect feedback active noise control (ANC) scheme based on the fundamental frequency estimation is proposed for systems with a harmonic noise. When reference signals necessary for feedforward ANC configuration is difficult to obtain, the conventional ANC algorithms for multi-tonal noise do not measure the reference signals but generate them with the estimated frequencies. However, the beating phenomena, in which certain frequency components of the noise vanish intermittently, may make the adaptive frequency estimation difficult. The confusion in the estimated frequencies due to the beating phenomena makes the generated reference signals worthless. The proposed algorithm consists of two parts. The first part is a reference generator using the fundamental frequency estimation and the second one is the conventional feedforward control. We propose the fundamental frequency estimation algorithm using decision rules, which is insensitive to the beating phenomena. In addition, the proposed fundamental frequency estimation algorithm has good tracking capability and lower variance of frequency estimation error than that of the conventional cascade ANF method. We are also able to control all interested modes of the noise, even which cannot be estimated by the conventional frequency estimation method because of the poor SIN ratio. We verify the performance of the proposed ANC method through simulations for the measured cabin noise of a passenger ship and the measured time-varying engine booming noise of a passenger vehicle.