• Title/Summary/Keyword: Robust algorithm

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A Study on The Adaptive Robust Servocontroller (견실한 서보적응제어기에 관한 연구)

  • 김종원
    • Transactions of the Korean Society of Mechanical Engineers
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    • v.14 no.3
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    • pp.513-525
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    • 1990
  • This paper presents Adaptive Robust Servocontrol(ARSC) scheme, which is an explicit(or indirect) pole-assignment adaptive algorithm with the property of "robustness". It guarantees asymptotic regulation and tracking in the presence of finite parameter perturbations of the unknown plant(or process) model. The controller structure is obtained by transforming a robust control theory into an adaptive control version. This controller structure is combined with the model estimation algorithm which includes a dead-zone for bounded noise. It is proved theoretically that this combination of control and identification is globally convergent and stable. It is also shown, through a real-time simulation study, that the desired closed-loop poles of the augmented system can be assigned directly, and that the adjustment mechanism of the scheme tunes the controller parameters according to the assigned closed-loop poles.oop poles.

Depth-hybrid speeded-up robust features (DH-SURF) for real-time RGB-D SLAM

  • Lee, Donghwa;Kim, Hyungjin;Jung, Sungwook;Myung, Hyun
    • Advances in robotics research
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    • v.2 no.1
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    • pp.33-44
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    • 2018
  • This paper presents a novel feature detection algorithm called depth-hybrid speeded-up robust features (DH-SURF) augmented by depth information in the speeded-up robust features (SURF) algorithm. In the keypoint detection part of classical SURF, the standard deviation of the Gaussian kernel is varied for its scale-invariance property, resulting in increased computational complexity. We propose a keypoint detection method with less variation of the standard deviation by using depth data from a red-green-blue depth (RGB-D) sensor. Our approach maintains a scale-invariance property while reducing computation time. An RGB-D simultaneous localization and mapping (SLAM) system uses a feature extraction method and depth data concurrently; thus, the system is well-suited for showing the performance of the DH-SURF method. DH-SURF was implemented on a central processing unit (CPU) and a graphics processing unit (GPU), respectively, and was validated through the real-time RGB-D SLAM.

Design of Robust Support Vector Machine Using Genetic Algorithm (유전자 알고리즘을 이용한 강인한 Support vector machine 설계)

  • Lee, Hee-Sung;Hong, Sung-Jun;Lee, Byung-Yun;Kim, Eun-Tai
    • Journal of the Korean Institute of Intelligent Systems
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    • v.20 no.3
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    • pp.375-379
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    • 2010
  • The support vector machine (SVM) has been widely used in variety pattern recognition problems applicable to recommendation systems due to its strong theoretical foundation and excellent empirical successes. However, SVM is sensitive to the presence of outliers since outlier points can have the largest margin loss and play a critical role in determining the decision hyperplane. For robust SVM, we limit the maximum value of margin loss which includes the non-convex optimization problem. Therefore, we proposed the design method of robust SVM using genetic algorithm (GA) which can solve the non-convex optimization problem. To demonstrate the performance of the proposed method, we perform experiments on various databases selected in UCI repository.

A Hybridization of Adaptive Genetic Algorithm and Particle Swarm Optimization for Numerical Optimization Functions

  • Yun, Young-Su;Gen, Mitsuo
    • Proceedings of the Korea Society for Industrial Systems Conference
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    • 2008.10b
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    • pp.463-467
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    • 2008
  • Heuristic optimization using hybrid algorithms have provided a robust and efficient approach for solving many optimization problems. In this paper, a new hybrid algorithm using adaptive genetic algorithm (aGA) and particle swarm optimization (PSO) is proposed. The proposed hybrid algorithm is applied to solve numerical optimization functions. The results are compared with those of GA and other conventional PSOs. Finally, the proposed hybrid algorithm outperforms others.

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A Domain-independent Dual-image based Robust Reversible Watermarking

  • Guo, Xuejing;Fang, Yixiang;Wang, Junxiang;Zeng, Wenchao;Zhao, Yi;Zhang, Tianzhu;Shi, Yun-Qing
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.12
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    • pp.4024-4041
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    • 2022
  • Robust reversible watermarking has attracted widespread attention in the field of information hiding in recent years. It should not only have robustness against attacks in transmission but also meet the reversibility of distortion-free transmission. According to our best knowledge, the most recent robust reversible watermarking methods adopt a single image as the carrier, which might lead to low efficiency in terms of carrier utilization. To address the issue, a novel dual-image robust reversible watermarking framework is proposed in this paper to effectively utilize the correlation between both carriers (namely dual images) and thus improve the efficiency of carrier utilization. In the dual-image robust reversible watermarking framework, a two-layer robust watermarking mechanism is designed to further improve the algorithm performances, i.e., embedding capacity and robustness. In addition, an optimization model is built to determine the parameters. Finally, the proposed framework is applied in different domains (namely domain-independent), i.e., Slantlet Transform and Singular Value Decomposition domain, and Zernike moments, respectively to demonstrate its effectiveness and generality. Experimental results demonstrate the superiority of the proposed dual-image robust reversible watermarking framework.

Performance Analysis of MAP Algorithm by Robust Equalization Techniques in Nongaussian Noise Channel (비가우시안 잡음 채널에서 Robust 등화기법을 이용한 터보 부호의 MAP 알고리즘 성능분석)

  • 소성열
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.25 no.9A
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    • pp.1290-1298
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    • 2000
  • Turbo Code decoder is an iterate decoding technology, which extracts extrinsic information from the bit to be decoded by calculating both forward and backward metrics, and uses the information to the next decoding step Turbo Code shows excellent performance, approaching Shannon Limit at the view of BER, when the size of Interleaver is big and iterate decoding is run enough. But it has the problems which are increased complexity and delay and difficulty of real-time processing due to Interleaver and iterate decoding. In this paper, it is analyzed that MAP(maximum a posteriori) algorithm which is used as one of Turbo Code decoding, and the factor which determines its performance. MAP algorithm proceeds iterate decoding by determining soft decision value through the environment and transition probability between all adjacent bits and received symbols. Therefore, to improve the performance of MAP algorithm, the trust between adjacent received symbols must be ensured. However, MAP algorithm itself, can not do any action for ensuring so the conclusion is that it is needed more algorithm, so to decrease iterate decoding. Consequently, MAP algorithm and Turbo Code performance are analyzed in the nongaussian channel applying Robust equalization technique in order to input more trusted information into MAP algorithm for the received symbols.

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A Study on the Robust Design Using Kriging Surrogate Models (크리깅 근사모델을 이용한 강건설계에 관한 연구)

  • Lee, Kwon-Hee;Cho, Yong-Chul;Park, Gyung-Jin
    • Proceedings of the KSME Conference
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    • 2004.11a
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    • pp.870-875
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    • 2004
  • Current trend of design technologies shows engineers to objectify or automate the given decision-making process. The numerical optimization is an example of such technologies. However, in numerical optimization, the uncertainties are uncontrollable to efficiently objectify or automate the process. To better manage these uncertainties, Taguchi method, reliability-based optimization and robust optimization are being used. To obtain the target performance with the maximum robustness is the main functional requirement of a mechanical system. In this research, the robust design strategy is developed based on the DACE and the global optimization approaches. The DACE modeling, known as the one of Kriging interpolation, is introduced to obtain the surrogate approximation model of the system. The robustness is determined by the DACE model to reduce the real function calculations. The simulated annealing algorithm of global optimization methods is adopted to determine the global robust design of a surrogated model. The mathematical problems and the MEMS design problem are investigated to show the validity of the proposed method.

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Research on Robust Stability Analysis and Worst Case Identification Methods for Parameters Uncertain Missiles

  • Hou, Zhenqian;Liang, Xiaogeng;Wang, Wenzheng
    • International Journal of Aeronautical and Space Sciences
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    • v.15 no.1
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    • pp.63-73
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    • 2014
  • For robust stability analysis of parameters uncertainty missiles, the traditional frequency domain method can only analyze each respective channel at several interval points within uncertain parameter space. Discontinuous calculation and couplings between channels will lead to inaccurate analysis results. A method based on the ${\nu}$-gap metric is proposed, which is able to comprehensively evaluate the robust stability of missiles with uncertain parameters; and then a genetic-simulated annealing hybrid optimization algorithm, which has global and local searching ability, is used to search for a parameters combination that leads to the worst stability within the space of uncertain parameters. Finally, the proposed method is used to analyze the robust stability of a re-entry missile with uncertain parameters; the results verify the feasibility and accuracy of the method.

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.

Design of a Robust Tracking Controller by the Estimation of Vibration Quantity (진동량 추정을 통한 강인 트랙킹 제어기의 설계)

  • Lee, Moon-Noh;Jin, Kyoung-Bog;Yun, Ki-Bong
    • Journal of Institute of Control, Robotics and Systems
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    • v.13 no.9
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    • pp.856-860
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    • 2007
  • This paper presents a robust tracking controller design method for the track-following system of an optical recording device. A tracking loop gain adjustment algorithm is introduced to accurately estimate the tracking vibration quantity in spite of the uncertainties of the tracking actuator. A minimum tracking open-loop gain is calculated by the estimated tracking vibration quantity and a tolerable limit of tracking error. A robust tracking controller is designed by considering a robust $H_\infty$ control problem with the weighting function of a slightly larger gain than the minimum tracking open-loop gain. The proposed controller design method is applied to the track-following system of an optical recording device and is evaluated through the experimental result.