• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 Proceedings of the Korea Automatic Control Conference, 11th (KACC); Pohang, Korea; 24-26 Oct. 1996
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• pp.177-180
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• 1996

The purpose of this paper is to design a robust adaptive control algorithm for a class of systems having continuous relay nonlinearity. This continuous relay nonlinearity can be defined as an analytic nonlinear function having unknown parameters and bounded unmodeling part. By this mathematical modeling, the whole system can be considered as a nonlinear system having unknown parameters and bounded perturbation. The control algorithm of this paper, RALC, can be constructed by robust adaptive law, feedback linearization, and indirect robust adaptive control. By this RALC, we can obtain that the output of given system can follow that of a stable reference linear model made by designer and the boundedness of all signals in closed-loop system can be maintained. Therefore, we can confirm a robust adaptive control for a class of systems having continuous relay nonlinearity.

• 수산해양기술연구
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• 제30권4호
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• pp.329-340
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• 1994

This paper presents a dynamic compensation methodology for robust trajectory tracking control of uncertain robot manipulators. To improve tracking performance of the system, a full model-based feedforward compensation with continuous VS-type robust control is developed in this paper(i.e,. robust decentralized adaptive control scheme). Since possible bounds of uncertainties are unknown, the adaptive bounds of the robust control is used to directly estimate the uncertainty bounds(instead of estimating manipulator parameters as in centralized adaptive control0. The global stability and robustness issues of the proposed control algorithm have been investigated extensively and rigorously via a Lyapunov method. The presented control algorithm guarantees that all system responses are uniformly ultimately bounded. Thus, it is shown that the control system is evaluated to be highly robust with respect to significant uncertainties.

• 제어로봇시스템학회논문지
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• 제5권6호
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• pp.656-666
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• 1999

In this paper, we design the optimal PD control system which has the robust performance. This PD control system is designed by applying genetic algorithm (GA) to the determination of proportional gain KP and derivative gain KD that are given by PD servo controller, to make the output of plant follow the output of reference model optimally. These proportional and derivatibe gains are simultaneously optimized in the search domain guaranteeing the robust performance of system. And, this PD control system is compared with $\mu$ -synthesis control system for the robust performance. The PD control system designed by the proposed method has not only the robust performance but also the better command tracking performance than that of the $\mu$ -synthesis control system. The effectiveness of this control system is verified by computer simulation.

• 제어로봇시스템학회논문지
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• 제7권4호
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• pp.362-368
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• 2001

We study on the velocity matching algorithm for transfer alignment of inertial navigation system(INS) using a robust H$_2$ filter. We suggest an uncertainty model and a discrete robust H$_2$filter for INS and apply the suggested robust H$_2$ filter to the uncertainty model. The discrete robust H$_2$filter is shown by simulation to have better performance time and accuracy than Kalman filter.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권9호
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• pp.4684-4705
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• 2019

Collaborative filtering recommender systems are vulnerable to shilling attacks in which malicious users may inject biased profiles to promote or demote a particular item being recommended. To tackle this problem, many robust collaborative recommendation methods have been presented. Unfortunately, the robustness of most methods is improved at the expense of prediction accuracy. In this paper, we construct a robust Bayesian probabilistic matrix factorization model for collaborative filtering recommender systems by incorporating the detection of user anomaly rating behaviors. We first detect the anomaly rating behaviors of users by the modified K-means algorithm and target item identification method to generate an indicator matrix of attack users. Then we incorporate the indicator matrix of attack users to construct a robust Bayesian probabilistic matrix factorization model and based on which a robust collaborative recommendation algorithm is devised. The experimental results on the MovieLens and Netflix datasets show that our model can significantly improve the robustness and recommendation accuracy compared with three baseline methods.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1990년도 추계학술대회 논문집 학회본부
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• pp.391-395
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• 1990

A new control algorithm is developed to achieve the robust performance of the system during the overall control process. Time-varying sliding manifolds are proposed to remove the reaching phase which is one of common shortcomings of variable structure control scheme. A necessary and sufficient condition for the existence of a sliding mode on the newly proposed time-varying sliding mode on the newly proposed time-varying sliding manifolds is derived by Lyapunov's second method. The digital simulation results show that the newly proposed control algorithm is superior to the typical variable structure control algorithm with respect to the robust performance of the system. The simplicity of the proposed control algorithm encourages control engineers to implement the proposed control algorithm in many control problems.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2005년도 춘계학술대회논문집
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• pp.164-169
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• 2005

Microphone array techniques are being used widely in wind tunnel measurements for identification of the distributed aerodynamic noise sources on the model being tested. Depending on the frequencies and sound levels, conventional beamforming algorithm has limitation in separating two adjacent sources. Several modifications to the classical beamforming have been developed to enhance way resolution and reduce sidelobe levels. In this Paper the robust adaptive beamforming and the CLEAN algorithm are used to compare to the result of conventional beamforming method. It is found that the CLEAN algorithm is capable of pin-pointing locations of multiple sources nearby, while these sources are unidentifiable with robust adaptive or conventional beamforming techniques.

• 정보보호학회논문지
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• 제7권3호
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• pp.65-78
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• 1997

DES가 Differential Cryptanalysis(이하 DC)에 쉽게 공격받을 수 있는 결정적인 취약점은 5-box를 포함한 암호함수의 구조에 있다 따라서 DES의 DC에 대한 대응방안으로는 XOR분포가 완전하게 균일(입력 XOR가 zero일 경우는 제외)하도록 5-box를 재구성하는 방법과 N-1 라운드 특성이 구성될 확률을 낮추기 위해 DES 알고리즘의 일부를 수정하는 방법을 생각할 수 있다. 그러나 Dawson과 Tavares가 제안한 완전히 균일한 XOR분포 테이블을 갖는 S-box는 오히려 균일하지 않을 매보다 더 취약하다고 Pieprzyk의 연구결과에 의해 증명되었다 결국 DES가 DC에 대응하기 위해서는 5-box의 재설계만으로는 부족하며 암호함수 자체를 수정해야 할 것이다. 본 논문에서는 DES의 암호함수를 일부 수정하여 DC에 대한 반복 특성이 구성될 확률을 낮추는 방안을 제안하고자 한다. 비교 분석 결과 제안된 알고리즘이 기존의 DES보다 DC 공격에 강함을 확인하였다.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.632-635
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• 2003

This paper describes a system fur tracking multiple faces in an input video sequence using facial convex hull based facial segmentation and robust hausdorff distance. The algorithm adapts skin color reference map in YCbCr color space and hair color reference map in RGB color space for classifying face region. Then, we obtain an initial face model with preprocessing and convex hull. For tracking, this algorithm computes displacement of the point set between frames using a robust hausdorff distance and the best possible displacement is selected. Finally, the initial face model is updated using the displacement. We provide an example to illustrate the proposed tracking algorithm, which efficiently tracks rotating and zooming faces as well as existing multiple faces in video sequences obtained from CCD camera.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1999년도 추계종합학술대회 논문집
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• pp.540-543
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• 1999

We propose a face tracking algorithm using skin-color based segmentation and a robust Hausdorff distance. First, we present L＊a＊b＊ color model and face segmentation algorithm. A face is segmented from the first frame of input video sequences using skin-color map. Then, we obtain an initial face model with Laplacian operator. For tracking, a robust Hausdorff distance is computed and the best possible displacement t. is selected. Finally, the previous face model is updated using the displacement t. It is robust to some noises and outliers. We provide an example to illustrate the proposed tracking algorithm in video sequences obtained from CCD camera.