• Title/Summary/Keyword: Noise Robust

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Design and Analysis of a Robust State Estimator Combining Perturbation Observer (섭동관측기를 연합한 강인 상태추정기 설계 및 해석)

  • Kwon SangJoo
    • Journal of Institute of Control, Robotics and Systems
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    • v.11 no.6
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    • pp.477-483
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    • 2005
  • This article describes a robust state estimation method which enables to produce reliable estimates in spite of heavy perturbation including plant uncertainty and external disturbances. The main idea is to combine the standard state estimator with the perturbation observer in the estimator frame. The perturbation observer reflects equivalent quantity of plant uncertainty and external disturbances during the estimation process so that the state estimator dynamics gets as close as possible to the real plant dynamics. The robust state estimator proposed in this paper is given in a recursive discrete-time form which is very useful fur implementation purpose. In terms of the error dynamics derived for the robust state estimator, we discuss the stability issue and noise sensitivity. The effectiveness and practicality of the robust state estimator are verified through numerical examples and experimental results.

Initial Robust Design of Deadweight 150,000 ton Bulk Carrier (재화중량 150,000톤 산적화물선의 초기 로버스트 설계)

  • Koh, Chang-Doo;Kim, Soo-Young
    • Journal of Ocean Engineering and Technology
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    • v.13 no.4 s.35
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    • pp.182-189
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    • 1999
  • The robust design technology which can determine design variables getting best performance function with insensitivity to the environment noise, is an important method for improving the performance of products at low cost. Applying the robust design technology in ship design, Koh et al[10] introduced the planing hull design. This paper reports the application this technology to a 150K bulk carrier which has many design variables and shows that the robust design technology is superior to optimization technique in practical use.

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Robust Design of Crankshaft (크랭크샤프트 강건 설계)

  • Lee, Seungwoo;Yang, Chulho
    • Transactions of the Korean Society of Automotive Engineers
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    • v.24 no.3
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    • pp.279-284
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    • 2016
  • Finite element analysis along with DOE scheme has been performed to obtain robust design of crankshaft assembly. This study focused on obtaining optimized fillet radius of crankshaft mainly by statistical approach. 27 design cases using 3 factors with 3 levels are constructed by design of experiment. Changes of design factors and noise factor may influence the durability of crankshaft system. General two stages of robust design may enhance the durability of crankshaft model. Increasing crank arm thickness was adopted as a shrink step and change of fillet radius was used as a shift step. By combining these two steps, the stress concentration at the fillet area is reduced and adequate fillet radius is determined for the robust design of crankshaft.

Robust Least Squares Motion Deblurring Using Inertial Sensor for Strapdown Image IR Sensors (스트랩다운 적외선 영상센서를 위한 관성센서 기반 강인최소자승 움직임 훼손영상 복원 기법)

  • Kim, Ki-Seung;Ra, Sung-Woong
    • Journal of Institute of Control, Robotics and Systems
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    • v.18 no.4
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    • pp.314-320
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    • 2012
  • This paper proposes a new robust motion deblurring filter using the inertial sensor measurements for strapdown image IR applications. With taking the PSF measurement error into account, the motion blurred image is modeled by the linear uncertain state space equation with the noise corrupted measurement matrix and the stochastic parameter uncertainty. This motivates us to solve the motion deblurring problem based on the recently developed robust least squares estimation theory. In order to suppress the ringing effect on the deblurred image, the robust least squares estimator is slightly modified by adoping the ridge-regression concept. Through the computer simulations using the actual IR scenes, it is demonstrated that the proposed algorithm shows superior and reliable motion deblurring performance even in the presence of time-varying motion artifact.

Analysis of Degradation Data Using Robust Experimental Design (강건 실험계획법을 이용한 열화자료의 분석)

  • 서순근;하천수
    • Journal of Korean Society for Quality Management
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    • v.32 no.1
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    • pp.113-129
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    • 2004
  • The reliability of the product can be improved by making the product less sensitive to noises. Especially, it Is important to make products robust against various noise factors encountered in production and field environments. In this paper, the phenomenon of degradation assumes a simple random coefficient degradation model to present analysis procedures of degradation data for robust experimental design. To alleviate weak points of previous studies, such as Taguchi's, Wasserman's, and pseudo failure time methods, novel techniques for analysis of degradation data using the cross array that regards amount of degradation as a dynamic characteristic for time are proposed. Analysis approach for degradation data using robust experimental design are classified by assumptions on parametric or nonparametric degradation rate(or slope). Also, a simulation study demonstrates the superiority of proposed methods over some previous works.

Multi-Level Response Surface Approximation for Large-Scale Robust Design Optimization Problems (다층분석법을 이용한 대규모 파라미터 설계 최적화)

  • Kim, Young-Jin
    • Korean Management Science Review
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    • v.24 no.2
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    • pp.73-80
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    • 2007
  • Robust Design(RD) is a cost-effective methodology to determine the optimal settings of control factors that make a product performance insensitive to the influence of noise factors. To better facilitate the robust design optimization, a dual response surface approach, which models both the process mean and standard deviation as separate response surfaces, has been successfully accepted by researchers and practitioners. However, the construction of response surface approximations has been limited to problems with only a few variables, mainly due to an excessive number of experimental runs necessary to fit sufficiently accurate models. In this regard, an innovative response surface approach has been proposed to investigate robust design optimization problems with larger number of variables. Response surfaces for process mean and standard deviation are partitioned and estimated based on the multi-level approximation method, which may reduce the number of experimental runs necessary for fitting response surface models to a great extent. The applicability and usefulness of proposed approach have been demonstrated through an illustrative example.

A Synchronization Scheme Based on Moving Average for Robust Audio Watermarking

  • Zhang, Jinquan;Han, Bin
    • Journal of Information Processing Systems
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    • v.15 no.2
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    • pp.271-287
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    • 2019
  • The synchronization scheme based on moving average is robust and suitable for the same rule to be adopted in embedding watermark and synchronization code, but the imperceptibility and search efficiency is seldom reported. The study aims to improve the original scheme for robust audio watermarking. Firstly, the survival of the algorithm from desynchronization attacks is improved. Secondly, the scheme is improved in inaudibility. Objective difference grade (ODG) of the marked audio is significantly changed. Thirdly, the imperceptibility of the scheme is analyzed and the derived result is close to experimental result. Fourthly, the selection of parameters is optimized based on experimental data. Fifthly, the search efficiency of the scheme is compared with those of other synchronization code schemes. The experimental results show that the proposed watermarking scheme allows the high audio quality and is robust to common attacks such as additive white Gaussian noise, requantization, resampling, low-pass filtering, random cropping, MP3 compression, jitter attack, and time scale modification. Moreover, the algorithm has the high search efficiency and low false alarm rate.

Noise-tolerant Image Restoration with Similarity-learned Fuzzy Association Memory

  • Park, Choong Shik
    • Journal of the Korea Society of Computer and Information
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    • v.25 no.3
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    • pp.51-55
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    • 2020
  • In this paper, an improved FAM is proposed by adopting similarity learning in the existing FAM (Fuzzy Associative Memory) used in image restoration. Image restoration refers to the recovery of the latent clean image from its noise-corrupted version. In serious application like face recognition, this process should be noise-tolerant, robust, fast, and scalable. The existing FAM is a simple single layered neural network that can be applied to this domain with its robust fuzzy control but has low capacity problem in real world applications. That similarity measure is implied to the connection strength of the FAM structure to minimize the root mean square error between the recovered and the original image. The efficacy of the proposed algorithm is verified with significant low error magnitude from random noise in our experiment.