• 전력전자학회논문지
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• 제3권3호
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• pp.206-213
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• 1998

본 논문에서는 유도전동기의 속응 토크제어를 위한 파라미터 변동의 적응보상기법을 제안하였다. 제어성능을 현저히 저하시키는 원인으로 작용하는 파라미터의 변동을 보상하기 위하여 본 논문에서는 모델기준 적응제어(MRAC)방식을 적용하여 회전자 저항값 변동을 추정 보상한다. 본 적응제어방식은 실측 순시무효전력과 추정 순시무효전력의 오차관계에서 실시간으로 회전자 저항값 변동을 추정 보상하는 방식이다. 본 방식은 전동기 파라미터를 사용하지 않고 실측 순시무효전력을 기준모델로 적용하기 때문에 전동기 등 등가모델에서 구한 기존의 다른 기준모델에 비해 강인한 시스템이 된다. 추정된 회전자 저항값을 이용하여 자속관측기를 구성하고 이를 직접베터 제어방식에 적용하였으며, 시뮬레이션 및 실험을 통하여 속응 토크제어가 원활히 수행됨을 입증하였다.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2000년도 춘계학술대회논문집
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• pp.56-63
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• 2000

Abstract - In this paper, an adaptive mechanism based on immune algorithm is designed and it is applied for the autonomous guided vehicle(AGV) driving. When the immune algorithm is applied to the PID controller, there exists the case that the plant is damaged due to the abrupt change of PID parameters since the parameters are adjusted almost randomly. To solve this problem, a neural network is used to model the plant and the parameter tuning of the model is performed by the immune algorithm. After the PID parameters are determined in this off-line manner, these gains are then applied to the plant for the on-line control using immune adaptive algorithm. Moreover, even though the neural network model may not be accurate enough intially, the weighting parameters are adjusted to be accurate through the on-line fine tuning. The computer simulation for the control of steering and speed of AGV is performed. The results show that the proposed controller has better performances than other conventional controllers.

• 한국정밀공학회지
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• 제21권10호
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• pp.65-77
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• 2004

In this paper, we propose an adaptive mechanism based on immune algorithm and neural network identifier technique. It is also applied fur an autonomous guided vehicle (AGV) system. When the immune algorithm is applied to the PID controller, there exists the case that the plant is damaged due to the abrupt change of PID parameters since the parameters are almost adjusted randomly. To solve this problem, we use the neural network identifier (NNI) technique fur modeling the plant and humoral immune algorithm (HIA) which performs the parameter tuning of the considered model, respectively. After the PID parameters are determined in this off-line manner, these gains are then applied to the plant for the on-line control using an immune adaptive algorithm. Moreover, even though the neural network model may not be accurate enough initially, the weighting parameters are adjusted to be accurate through the on-line fine tuning. Finally, the simulation and experimental result fur the control of steering and speed of AGV system illustrate the validity of the proposed control scheme. These results for the proposed method also show that it has better performance than other conventional controller design methods.

• 대한전기학회논문지:시스템및제어부문D
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• 제49권4호
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• pp.201-212
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• 2000

In this paper, an adaptive mechanism based on immune algorithm is designed and it is applied for the autonomous guided vehicle(AGV) driving. When the immune algorithm is applied to the PID controller, there exists the cast that the plant is damaged due to the abrupt change of PID parameters since the parameters are adjusted almost randomly. To solve this problem, a neural network is used to model the plant and the parameter tuning of the model is performed by the immune algorithm. After the PID parameters are determined in this off-line manner, these gains are then applied to the plant for the on-line control using immune adaptive algorithm. Moreover, even though the neural network model may not be accurate enough intially, the weighting parameters are adjusted to be accurate through the on-line fine tuning. The computer simulation for the control of steering and speed of AGV is performed. The results show that the proposed controller has better performances than other conventional controllers.

• 제어로봇시스템학회논문지
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• 제22권5호
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• pp.315-319
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• 2016

This paper proposes a simple adaptive sliding mode control algorithm for controlling a permanent magnet synchronous generator (PMSG) of a MW-class direct-driven wind turbine system. The proposed adaptive sliding mode controller does not require accurate knowledge of the PMSG parameter or turbine torque values. The proposed controller can accurately track the reference angular speed computed by the maximum power point tracking(MPPT) algorithm. Finally, this paper gives Matlab/Simulink simulation results to verify the practicality and effectiveness of the proposed adaptive sliding mode controller.

• 대한전기학회논문지
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• 제41권3호
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• pp.311-319
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• 1992

In this paper, a direct adaptive pole placement controller for an unknown linear time-invariant single-input single-output nonminimum phase plant is proposed. To design this direct adaptive pole placement controller, the auxiliary signals are introduced. Consequently, a linear equation error model is formulated for estimating both the controller parameters and the additional auxiliary parameters. To estimate the controller parameters and the additional auxiliary parameters, the exponentially weighted least-squares algorithm is implemented, and a method of selecting the characteristic polynomials of the sensitivity function filters is proposed. In this method, all the past measurement data are weighted exponentially. A series of simulations for a nonminimum phase plant is presented to illustrate some features of both the parameter estimation and the output response of this adaptive pole placement controller.

• Journal of Advanced Marine Engineering and Technology
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• 제38권10호
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• pp.1318-1326
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• 2014

The purpose of a tracking control system is to track a moving target and to find the exact information of the target. If the platform of the tracking control system is equipped on a moving vehicle such as a ship, the tracking control system will treat even the additional platform motion. In order to avoid the complexity comprising the tracking control system, a process to treat the platform motion, named stabilizing system, must be separated from the tracking control system. In this paper, a method to comprise an attitude control system for the platform stabilization is proposed using an adaptive fuzzy control which is applicable to the system with structural and parametric uncertainty. The suggested adaptive fuzzy control algorithm is the 2nd/1st-type indirect adaptive fuzzy control algorithm using the advantages of 1st-type and 2nd-type indirect adaptive fuzzy control algorithm. Several experiments using the implemented stabilizing system are executed for verifying the effectiveness of the suggested method.

• 한국위성정보통신학회논문지
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• 제9권4호
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• pp.91-96
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• 2014

본 논문은 적외선 열영상에서 영상의 밝기와 대비 변화에 따라 적응적으로 화염 후보 영역을 검출하기 위한 적응 문턱치를 제안한다. 현장에 사용 되고 있는 화재 검출 시스템은 카메라의 설치 장소에 따라 얻어지는 영상의 밝기나 대비의 변화가 발생 하여 고정된 문턱치를 적용하는 화재 검출 알고리즘의 성능이 변화하게 되므로 환경에 적응적인 문턱치가 필요하다. 제안하는 적응 문턱치를 이용한 화염 검출 알고리즘은 화염의 특성인 온도와 동적임 특성을 분석하여 화염을 검출 한다. 실험을 위해 고정 문턱치를 이용한 화염 검출 알고리즘과 비교 하였으며 제안된 적응 문턱치를 이용한 화염 검출 알고리즘은 화염 검출률 91.42%이며 고정 문턱치를 적용 하였을 때 보다 오검출률을 약 20%가 감소한다. 그리고 영상의 밝기와 대비 변화에 의한 검출 결과가 일정함을 보여 준다.

• 대한조선학회논문집
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• 제31권2호
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• pp.38-44
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• 1994

1960년대 Auto-Pilot 시스템이 대양을 항해하는 선박에 장착되면서 운항경제성 및 선원 승선감의 견지에서 Auto-Pilot시스템의 제어 알고리듬이 연구되기 시작하였다. 초기에는 PD제어로 시작하였으나 잦은 타동작으로 인한 기구 마모를 줄이기 위해 실제 선수각과 설정선수방위 차가 어느 상한치 이상에서만 타각을 조작하는 on-off 제어를 도입하였다. 본 논문에서는 Auto-Pilot 시스템의 제어 알고리듬에 optimal제어, adaptive제어 등을 적용하여 제어기법간의 비교를 cost function을 통하여 수행함으로써 Auto-Pilot 시스템에 대한 최적의 제어기법을 조사하였다. Adaptive 제어를 위한 선박 조종운동방정식의 parameterization 과정을 검토하였고 adaptive 알고리듬의 장점이 파라미터 추정이 잘못된 경우의 수치시뮬레이션 결과로부터 분명히 알 수 있었다.

• International Journal of Control, Automation, and Systems
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• 제6권6호
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• pp.818-827
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• 2008

In this paper, we propose a new noise estimation and reduction algorithm for stationary and nonstationary noisy environments. This approach uses an algorithm that classifies the speech and noise signal contributions in time-frequency bins. It relies on the ratio of the normalized standard deviation of the noisy power spectrum in time-frequency bins to its average. If the ratio is greater than an adaptive estimator, speech is considered to be present. The propose method uses an auto control parameter for an adaptive estimator to work well in highly nonstationary noisy environments. The auto control parameter is controlled by a linear function using a posteriori signal to noise ratio(SNR) according to the increase or the decrease of the noise level. The estimated clean speech power spectrum is obtained by a modified gain function and the updated noisy power spectrum of the time-frequency bin. This new algorithm has the advantages of much more simplicity and light computational load for estimating the stationary and nonstationary noise environments. The proposed algorithm is superior to conventional methods. To evaluate the algorithm's performance, we test it using the NOIZEUS database, and use the segment signal-to-noise ratio(SNR) and ITU-T P.835 as evaluation criteria.