• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 하계종합학술대회 논문집(4)
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• pp.123-126
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• 2000

In this paper, we propose new watermarking technique using weighting factor decision method in the watermark embedding step and adaptive threshold decision method in the watermark extracting step. In our method, we are determined weighting factor in simple by calculating distance between pixel coefficient and neighborhood pixel coefficients and threshold is adaptively determined by searching the minimized extract error value using histogram of difference value.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1990년도 하계학술대회 논문집
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• pp.43-46
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• 1990

A general scheme for a discrete adaptive observer having exponetial weighting properties is presented for a single-input single-output linear system. In this scheme, all the past measurement data are weighted esponetially both with the weighting factor and the stable matrix F. This observer is then implemented in the design of an indirect adaptive pole placement contoller. To increase nemerical stability in getting the controller parameter, a recusive algorithm is introduced. It is shown that the overall control scheme is globally stable with the persistent excition

• 대한전기학회:학술대회논문집
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• 대한전기학회 1990년도 하계학술대회 논문집
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• pp.51-54
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• 1990

A parametrization for a linear system is presented to design a direct model reference adaptive pole placement controler. This parametrized model is one of the structured nonminimal models. The exponentially weighted least-squres algorithm is employed to estimate the control parameters. The direct adaptive controller has the exponential weighting properties by the proposed method of selecting the characteristic polynomials of the sensitivity function filters in connection with the reference models.

• 한국인터넷방송통신학회논문지
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• 제10권4호
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• pp.137-143
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• 2010

본 논문은 채널에서 발생되는 진폭과 위상 찌그러짐을 보상하기위한 MCMA (Modified Constant Modulus Algorithm)의 비용 함수에서 weighting factor에 의한 자기 적응 등화의 성능을 비교한 것이다. MCMA 는 기존 방식인 CMA 의 비용 함수를 개선하여 등화기의 출력에서 진폭과 위상에 대한 오차 함수를 최소화할 수 있으며, 이때 weighting factor 의 값이 이용된다. 등화기의 성능을 비교할 때 initial state와 steady state로 분류하고 미리 정해진 레벨까지의 수렴 시간과 수렴 속도 및 안정된 등화 상태를 나타내며, 이들은 weighting factor에 의해 결정된다. 컴퓨터 시뮬레이션을 통하여 weighting factor에 따라 이들 2 가지 state 에 대한 각각 상이한 결과를 확인할 수 있었다. 본 결과를 이용하여 사용되는 통신 채널의 환경에 따라 weighting factor 값을 적절히 선택한다면 고품질의 디지털 정보 전송이 가능하게 될 것으로 기대된다.

• 한국인터넷방송통신학회논문지
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• 제13권3호
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• pp.55-61
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• 2013

본 논문에서는 통신 채널에서 발생되는 찌그러짐과 잡음의 영향을 최소화하기 위하여 사용되는 S-MMA 적응 등화 알고리즘에서 Slice 가중치에 따른 성능을 비교하였다. 기존의 MMA 알고리즘에서는 등화기의 출력 신호와 송신 신호의 dispersion 상수만을 이용하지만, S-MMA에서는 등화기 출력 신호와 dispersion 상수외에 결정 장치의 출력 신호를 slice 상수만큼 고려하여 채널의 진폭과 위상 찌그러짐을 동시에 보상할 수 있다. 이때 slice 가중치가 적응 등화 알고리즘의 성능에 미치는 영향을 컴퓨터 시뮬레이션을 통해 확인하며, 성능 지수로는 등화기 출력 신호 성상도, 수렴 특성을 나타내는 잔류 isi, 최대 찌그러짐, MSE와 채널의 신호대 잡음비에 따른 SER을 사용하였다. 시뮬레이션 결과 slice 가중치가 적으면 잔류isi, 최대 찌그러짐과 MSE 성능이 우월하며, 가중치가 큰 경우 SER 성능이 우월함을 확인하였다.

• 드라이브 ㆍ 컨트롤
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• 제17권1호
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• pp.13-20
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• 2020

Adaptive neural networks based lateral controller is presented to guarantee path following performance for vehicle lane keeping in the presence of parameter time-varying characteristics of the vehicle lateral dynamics due to the road surface condition, load distribution, tire pressure and so on. The proposed adaptive controller could compensate vehicle lateral dynamics deviated from nominal dynamics resulting from parameter variations by incorporating it with neural networks that have the ability to approximate any given nonlinear function by adjusting weighting matrices. The controller is derived by using Lyapunov-based approach, which provides adaptive update rules for weighting matrices of neural networks. To show the superiority of the presented adaptive neural networks controller, the simulation results are given while comparing with backstepping controller chosen as the baseline controller. According to the simulation results, it is shown that the proposed controller can effectively keep the vehicle tracking the pre-given trajectory in high velocity and curvature with much accuracy under parameter variations.

• 한국정보통신학회논문지
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• 제4권3호
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• pp.603-610
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• 2000

본 논문에서는 직접 적응제어기와 간접 적응제어기를 Lyapunov 안정도 이론에 근거하여 결합하였다. 제어기는 RBF 신경망을 이용하여 구성하였으며 하중파라미터들은 적응칙에 의하여 조정되도록 하였다. 또한 시스템의 성능에 영향을 미치는 결합 가중치는 퍼지 If-THEN 규칙을 이용하여 결정되도록 하였다. 이렇게 함으로써 직접 적응제어기와 간접 적응제어기의 장점을 지니는 직 간접 혼합 신경망 적응제어기를 구성할 수 있었다. 제안한 알고리즘의 효용성을 보이기 위하여 일축 강페 로봇 매니퓰레이터를 대상으로 시뮬레이션한 결과 만족할 만한 성능을 보였다.

• Transactions on Control, Automation and Systems Engineering
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• 제3권2호
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• pp.117-123
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• 2001

To improve control performance of a non-linear system, many other reserches have used the sliding model control algorithm. The sliding mode controller is known to be robust against nonlinear and unmodeled dynamic terms. However, this algorithm raises the inherent chattering caused by excessive switching inputs around the sliding surface. Therefore, in order to solve the chattering problem and improve control performance, this study has developed the sliding mode controller with a perturbation estimator using the observer-based fuzzy adaptive network. The perturbation estimator based on the fuzzy adaptive network generates the control input of compensating unmodeled dynamics terms and disturbance. And the weighting parameters of the fuzzy adaptive network are updated on-line by adaptive law in order to force the estimation errors converge to zero. Therefore, the combination of sliding mode control and fuzzy adaptive network gives rise to the robust and intelligent routine. For evaluation control performance of the proposed approach, tracking control simulation is carried is carried out for the hydraulic motion simulator which is a 6-degree of freedom parallel manipulator.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 학술대회 논문집 정보 및 제어부문
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• pp.162-164
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• 2004

This paper proposes a new classification system combining the adaptive feature weighting algorithm using the genetic algorithm and the modified KNN rule. GA is employed to choose the middle value of weights and weights of features for high performance of the system. The modified KNN rule is proposed to estimate the class of test pattern using adaptive feature space. Experiments with the unconstrained handwritten digit database of Concordia University in Canada are conducted to show the performance of the proposed method.

• Journal of Power Electronics
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• 제13권1호
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• pp.122-138
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• 2013

Adaptive control of a peak current mode controlled (PCM) boost converter supplied by a PEM fuel cell is described in this paper. The adaptive controller with reference model and signal adaptation is developed in order to compensate the deviation of the response during the change of the operating point. The procedure for determining the adaptive algorithm's weighting coefficients, based on a combination of the pole-zero placement method and an optimization method is proposed. After applying the proposed procedure, the optimal adaptive algorithm's weighting coefficients can be determined in just a few iterations, without the use of a computer, thus greatly facilitating the application of the algorithm in real systems. Simulation and experimental results show that the dynamic behavior of a highly nonlinear control system with a fuel cell and a PCM boost converter, can fairly accurately be described by the dynamic behavior of the reference model, i.e., a linear system with constant parameters.