• 제목/요약/키워드: Adaptive adjustment

검색결과 136건 처리시간 0.021초

콘크리트 압축강도 추정을 위한 적응적 확률신경망 기법 (Adaptive Probabilistic Neural Network for Prediction of Compressive Strength of Concrete)

  • 김두기;이종재;장성규
    • 한국전산구조공학회:학술대회논문집
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    • 한국전산구조공학회 2004년도 가을 학술발표회 논문집
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    • pp.542-549
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    • 2004
  • The compressive strength of concrete is commonly used criterion in producing concrete. However, the tests on the compressive strength are complicated and time-consuming. More importantly, it is too late to make improvement even if the test result does not satisfy the required strength, since the test is usually performed at the 28th day after the placement of concrete at the construction site. Therefore, accurate and realistic strength estimation before the placement of concrete is being highly required. In this study, the estimation of the compressive strength of concrete was performed by probabilistic neural network (PNN) on the basis of concrete mix proportions. The estimation performance of PNN was improved by considering the correlation between input data and targeted output value. Adaptive probabilistic neural network (APNN) was proposed to automatically calculate the smoothing parameter in the conventional PNN by using the scheme of dynamic decay adjustment algorithm. The conventional PNN and APNN were applied to predict the compressive strength of concrete using actual test data of a concrete company. APNN showed better results than the conventional PNN in predicting the compressive strength of concrete.

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Performance Analysis of an Improved NLMS Algorithm

  • Tsuda, Yusuke;Shimamura, Tetsuya
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2002년도 ITC-CSCC -3
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    • pp.1475-1478
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    • 2002
  • This paper presents a performance analysis of an improved adaptive algorithm proposed by the authors recently. It is based on the normalized least mean square (NLMS) algorithm, which Is one of the major techniques to adapt the cofficients of a transversal filter. Generally, the performance of an adaptive algorithm is often discussed by investigating the mis-adjustment. In this paper, unlike these approaches, a novel analytical method is considered. letting the parameters so that the residual mean square error (MSE) after the convergence of the algorithm is equal to that of the NLMS algorithm, the MSE level is compared. It is shown that the theoretical analysis is agreed with the simulation results.

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RBFN을 이용한 로봇 매뉴퓰레이터의 실시간 제어 (The Neuro-Adaptive Control of Robotic Manipulators using RBFN)

  • 김정대;이민중;최영규;김성신
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1999년도 하계학술대회 논문집 G
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    • pp.2992-2994
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    • 1999
  • This paper investigates the direct adaptive control of nonlinear systems using RBFN(radial basis function networks). The structure of the controller consists of a fixed PD controller and a RBFN controller in parallel. An adaptation law for the weight adjustment is developed based on the Lyapunov stability theory to guarantee the stability of the overall control scheme. Also, the tracking errors between the system outputs and the desired outputs converge to zero asymptotically. To evaluate the performance of the controller, the proposed method is applied to the trajectory control of the two-link manipulator.

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유압 서보계의 $\delta$연산자를 이용한 모델기준형적응제어 (Model Reference Adaptive Control Using $\delta$-Operator of Hydraulic Servosystem)

  • 김기홍;윤일로;염만오
    • 한국정밀공학회지
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    • 제17권11호
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    • pp.151-157
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    • 2000
  • The MRAC theory has proved to be one of the most popular algorithms in the field of adaptive control, particularly for practical application to devices such as an hydraulic servosystem of which parameters are unknown or varying during operation. For small sampling period, the discrete time system becomes a nonminimal phase system. The $\delta$-MRAC was introduced to obtain the control performance of nonminimal phase system, because the z-MRAC can not control the plant for small sampling period. In this paper, $\delta$-MRAC is applied to the control of an hydraulic servosystem which is composed of servovalve, hydraulic cylinder and inertia load.

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A Block-Based Adaptive Data Hiding Approach Using Pixel Value Difference and LSB Substitution to Secure E-Governance Documents

  • Halder, Tanmoy;Karforma, Sunil;Mandal, Rupali
    • Journal of Information Processing Systems
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    • 제15권2호
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    • pp.261-270
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    • 2019
  • In order to protect secret digital documents against vulnerabilities while communicating, steganography algorithms are applied. It protects a digital file from unauthorized access by hiding the entire content. Pixel-value-difference being a method from spatial domain steganography utilizes the difference gap between neighbor pixels to fulfill the same. The proposed approach is a block-wise embedding process where blocks of variable size are chosen from the cover image, therefore, a stream of secret digital contents is hidden. Least significant bit (LSB) substitution method is applied as an adaptive mechanism and optimal pixel adjustment process (OPAP) is used to minimize the error rate. The proposed application succeeds to maintain good hiding capacity and better signal-to-noise ratio when compared against other existing methods. Any means of digital communication specially e-Governance applications could be highly benefited from this approach.

A Design of Controller for 4-Wheel 2-D.O.F. Mobile Robot Using Fuzzy-Genetic algorithms

  • Kim, Sangwon;Kim, Sunghoe;Sunho Cho;chongkug
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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    • pp.607-612
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    • 1998
  • In this paper, a controller using fuzzy-genetic algorithms is proposed for pat-tracking of WMR. A fuzzy controller is implemented so as to adjust appropriate crossover rate and mutation rate. A genetic algorithms is also implemented to have adaptive adjustment of control gain during optimizing process. To check effectiveness of this algorithms, computer simulation is applied.

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훈련 데이터세트의 조절을 통한 딥러닝 기반 Super-Resolution 의 성능 향상 (Performance Enhancement of Deep Learning-based Super-Resolution by Adjustment of Training Dataset)

  • 권기택;서영호
    • 한국방송∙미디어공학회:학술대회논문집
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    • 한국방송∙미디어공학회 2021년도 추계학술대회
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    • pp.218-220
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    • 2021
  • 본 논문에서는 CAR(content adaptive resampler)로 축소된 저해상도 이미지를 직접 다른 모델에 여러가지 방식으로 훈련을 시켜 성능을 개선시키고자 하였다. 본 논문에서는 단일 영상 super resolution 에 관하여 여러 기술이 존재하는 상황에 더 나은 기술을 테스트하려 하고 그를 위해 과거의 모델들에 대한 이해가 필요하여 이를 구현하였다. 현재 가장 뛰어난 성능을 보이고 있는 모델 중의 하나인 CAR 에서 복원 전 이미지를 사용하여 훈련을 시키면 더 나은 성능의 모델을 만들 수 있을 것이라고 가정하고 다양한 훈련을 통해 성능을 개선시키고자 하였다.

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태양광 컨버터 시스템의 과도응답 개선을 위한 비선형 적응제어 및 안정성 해석 (Nonlinear Adaptive Control and Stability Analysis for Improving Transient Response of Photovoltaic Converter Systems)

  • 조현철;유수복;이권순
    • 제어로봇시스템학회논문지
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    • 제15권12호
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    • pp.1175-1183
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    • 2009
  • In photovoltaic(PV) generator systems, DC-DC converters are significantly considered for control system performance in power quality point of view. This paper presents a novel adaptive control method for DC-DC converters applied in PV generator systems. First, we derive a state-space average model of the converter system and then propose a reset control methodology to enhance transient response performance for time-varying PV systems. For estimating parameters of a reset control, a gradient descent optimization is utilized and an adjustment rule of them are derived respectively. An objective of the optimization is that characteristic equation of an augmented system model which is formed with an converter system model and an reset control is to trace a predefined polynomial given as a reference characteristic model. Next, we accomplish stability analysis by means of a well-known Lyapunov theory for nonlinear converter systems including time-varying voltage excitation from a PV generator. Numerical simulation demonstrates reliability of our control methodology and its superiority by comparison to a traditional control strategy.

Robust Deadbeat Current Control Method for Three-Phase Voltage-Source Active Power Filter

  • Nishida, Katsumi;Ahmed, Tarek;Nakaoka, Mutsuo
    • Journal of Power Electronics
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    • 제4권2호
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    • pp.102-111
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    • 2004
  • This paper is concerned with a deadbeat current control implementation of shunt-type three-phase active power filter (APF). Although the one-dimensional deadbeat control method can attain time-optimal response of APF compensating current, one sampling period is actually required fur its settling time. This delay is a serious drawback for this control technique. To cancel such a delay and one more delay caused by DSP execution time, the desired APF compensating current has to be predicted two sampling periods ahead. Therefore an adaptive predictor is adopted for the purpose of both predicting the control error of two sampling periods ahead and bringing the robustness to the deadbeat current control system. By adding the adaptive predictor output as an adjustment term to the reference value of half a source voltage period before, settling time is made short in a transient state. On the other hand, in a steady state, THD (total harmonic distortion) of the utility grid side AC source current can be reduced as much as possible, compared to the case that ideal identification of controlled system could be made.

적응형 퍼지-칼만 필터를 이용한 자세추정 성능향상 (Performance Enhancement of Attitude Estimation using Adaptive Fuzzy-Kalman Filter)

  • 김수대;백경동;김태림;김성신
    • 한국정보통신학회논문지
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    • 제15권12호
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    • pp.2511-2520
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    • 2011
  • 본 논문은 다중 센서 융합의 성능을 높이기 위해 적응형 퍼지-칼만 필터를 적용하고 교차검증법(cross-validation)으로 퍼지시스템 입 출력 소속 함수의 매개변수를 조정하는 방법을 제안한다. 적응형 퍼지-칼만 필터는 가속도의 변화량과 칼만 필터의 잔여오차를 입력으로 시스템잡음, 측정잡음을 추정하여 칼만 이득을 변화시킨다. 적용된 퍼지-칼만 필터는 잡음들을 가우시안 분포로 가정한 이전 방법과 비교하여 비선형/비가우시안 잡음에 강인한 추정 결과를 보여준다. 본 논문에서 제안한 퍼지-칼만 필터를 평가하기 위해 가속도센서/자이로센서를 융합하여 2축 자세추정시스템(Attitude Heading Reference System)을 설계하였고 무인항공기에 사용되는 자세추정센서 NAV420CA-100과 비교하여 성능을 검증하였다.