• Title/Summary/Keyword: adaptive method

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Adaptive line Enhancement by Using Adaptive Observer (적응 관측자를 사용한 ALE)

  • 최종호;이하정;이상욱
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.36 no.11
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    • pp.819-825
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    • 1987
  • The ALE problem, which tries to recover a sinusoidal signal corrupted by noise, has been solved using FIR filters. Recently several methods have been proposed using a norch filter of IIR type. In this study, the notch filter was represented with a parameter and auxiliary signals were generated by using an adaptive observer. A simple method is proposed to estimate the parameter. This method is tested under various circumstances by changing the input frequency, S/N ratio, and the type of the noise. The simulation shows that this method gives much better results than the other known methods with respect to the input S/N ratio and converging times. This method is simple and does not require much conputation, so it can be easily implemented in real time applications.

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A study on the power system stabilizer using discrete-time adaptive sliding mode control (이산 적응슬라이딩 모드 제어를 이용항 전력계통 안정화 장치에 관한 연구)

  • Park, Young-Moon;Kim, Wook
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.45 no.2
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    • pp.175-184
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    • 1996
  • In this paper the newly developed discrete-time adaptive sliding mode control method is proposed and applied to the power system stabilization problem. In contrast to the conventional continuous-time sliding mode controller, the proposed method is developed in the discrete-time domain and based on the input/output measurements instead of the continuous-time and the full-states feedback, respectively. Because the proposed control method has the adaptivity property in addition to the natural robustness property of the sliding mode control, it is possible to design the power system stabilizer which can overcome both the minor variations of the parameters of the power system and the diverse operating conditions and faults of the power system. Mathematical proof and the various computer simulations are done to verify the performance and stability of the proposed method.

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AN INTERFERENCE FRINGE REMOVAL METHOD BASED ON MULTI-SCALE DECOMPOSITION AND ADAPTIVE PARTITIONING FOR NVST IMAGES

  • Li, Yongchun;Zheng, Sheng;Huang, Yao;Liu, Dejian
    • Journal of The Korean Astronomical Society
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    • v.52 no.2
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    • pp.49-55
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    • 2019
  • The New Vacuum Solar Telescope (NVST) is the largest solar telescope in China. When using CCDs for imaging, equal-thickness fringes caused by thin-film interference can occur. Such fringes reduce the quality of NVST data but cannot be removed using standard flat fielding. In this paper, a correction method based on multi-scale decomposition and adaptive partitioning is proposed. The original image is decomposed into several sub-scales by multi-scale decomposition. The region containing fringes is found and divided by an adaptive partitioning method. The interference fringes are then filtered by a frequency-domain Gaussian filter on every partitioned image. Our analysis shows that this method can effectively remove the interference fringes from a solar image while preserving useful information.

Visual Attention Detection By Adaptive Non-Local Filter

  • Anh, Dao Nam
    • IEIE Transactions on Smart Processing and Computing
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    • v.5 no.1
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    • pp.49-54
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    • 2016
  • Regarding global and local factors of a set of features, a given single image or multiple images is a common approach in image processing. This paper introduces an application of an adaptive version of non-local filter whose original version searches non-local similarity for removing noise. Since most images involve texture partner in both foreground and background, extraction of signified regions with texture is a challenging task. Aiming to the detection of visual attention regions for images with texture, we present the contrast analysis of image patches located in a whole image but not nearby with assistance of the adaptive filter for estimation of non-local divergence. The method allows extraction of signified regions with texture of images of wild life. Experimental results for a benchmark demonstrate the ability of the proposed method to deal with the mentioned challenge.

Asymptotically Stable Adaptive Load Torque Observer for Precision Position Control of BLDC Motor

  • 고종선
    • Proceedings of the KIPE Conference
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    • 1997.07a
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    • pp.97-100
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    • 1997
  • A new control method for the robust position control of a brushless DC(BLDC) motor using the asymptotically stable adaptive load torque observer is presented. A precision position control is obtained for the BLDC motor system approximately linearized using the field-orientation method. And the application of the load torque observer is published in [1] using fixed gain. However, the flux linkage is not exactly known for a load torque observer. Therefore, a model reference adaptive observer is considered to overcome the problem of the unknown parameter in this paper. And stability analysis is carried out using Liapunov stability theorem. As a result, asymptotically stable observer gain can be obtained without affecting the overall system response. The load disturbance detected by the asymptotically stable adaptive observer is compensated by feedforwarding the equivalent current having the fast response.

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A DATA COMPRESSION METHOD USING ADAPTIVE BINARY ARITHMETIC CODING AND FUZZY LOGIC

  • Jou, Jer-Min;Chen, Pei-Yin
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1998.06a
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    • pp.756-761
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    • 1998
  • This paper describes an in-line lossless data compression method using adaptive binary arithmetic coding. To achieve better compression efficiency , we employ an adaptive fuzzy -tuning modeler, which uses fuzzy inference to deal with the problem of conditional probability estimation. The design is simple, fast and suitable for VLSI implementation because we adopt the table -look-up approach. As compared with the out-comes of other lossless coding schemes, our results are good and satisfactory for various types of source data.

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An Adaptive Vendor Managed Inventory Model Using Action-Reward Learning Method (행동-보상 학습 기법을 이용한 적응형 VMI 모형)

  • Kim Chang-Ouk;Baek Jun-Geol;Choi Jin-Sung;Kwon Ick-Hyun
    • Journal of the Korean Operations Research and Management Science Society
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    • v.31 no.3
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    • pp.27-40
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    • 2006
  • Today's customer demands in supply chains tend to change quickly, variously even in a short time Interval. The uncertainties of customer demands make it difficult for supply chains to achieve efficient inventory replenishment, resulting in loosing sales opportunity or keeping excessive chain wide inventories. Un this paper, we propose an adaptive vendor managed inventory (VMI) model for a two-echelon supply chain with non-stationary customer demands using the action-reward learning method. The Purpose of this model is to decrease the inventory cost adaptively. The control Parameter, a compensation factor, is designed to adaptively change as customer demand pattern changes. A simulation-based experiment was performed to compare the performance of the adaptive VMI model.

An Empirical Study on Supply Chain Demand Forecasting Using Adaptive Exponential Smoothing (적응적 지수평활법을 이용한 공급망 수요예측의 실증분석)

  • Kim, Jeong-Il;Cha, Gyeong-Cheon;Jeon, Deok-Bin;Park, Dae-Geun;Park, Seong-Ho;Park, Myeong-Hwan
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2005.05a
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    • pp.658-663
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    • 2005
  • This study presents the empirical results of comparing several demand forecasting methods for Supply Chain Management(SCM). Adaptive exponential smoothing using change detection statistics (Jun) is compared with Trigg and Leach's adaptive methods and SAS time series forecasting systems using weekly SCM demand data. The results show that Jun's method is superior to others in terms of one-step-ahead forecast error and eight-step-ahead forecast error. Based on the results, we conclude that the forecasting performance of SCM solution can be improved by the proposed adaptive forecasting method.

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Leader-following Approach Based Adaptive Formation Control for Mobile Robots with Unknown Parameters (미지의 파라미터를 갖는 이동 로봇들을 위한 선도-추종 방법 기반 적응 군집 제어)

  • Moon, Ssurey;Park, Bong-Seok;Choi, Yoon-Ho;Park, Jin-Bae
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.60 no.8
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    • pp.1592-1598
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    • 2011
  • In this paper, a formation control method based on the leader-following approach for nonholonomic mobile robots is proposed. In the previous works, it is assumed that the followers know the leader's velocity by means of communication. However, it is difficult that the followers correctly know the leader's velocity due to the contamination or delay of information. Thus, in this paper, an adaptive approach based on the parameter projection algorithm is proposed to estimate the leader's velocity. Moreover, the adaptive backstepping technique is used to compensate the effects of a dynamic model with the unknown time-invariant and time-varying parameters. From the Lyapunov stability theory, it is proved that the errors of the closed-loop system are uniformly ultimately bounded. Simulation results illustrate the effectiveness of the proposed control method.

Adaptive Sliding Mode Control Design for Mismatched Uncertain Systems (비정합 불확실성을 갖는 시스템을 위한 적응 슬라이딩 모드 제어기 설계)

  • Choi, Han-Ho
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.24 no.2
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    • pp.39-43
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    • 2010
  • This paper presents an LMI-based method to design an adaptive sliding mode controller for a class of uncertain systems. In terms of LMIs an existence condition of a sliding surface is derived. And an adaptive switching feedback control law to guarantee the asymptotic stability as well as to estimate the norm bound of disturbances is proposed. Finally, a numerical design example for controlling a overhead crane model is given to show the effectiveness of the proposed method.