• Title/Summary/Keyword: Descent

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Numerical Optimization Applied to Estimate the Composition of Nonlinear Electric Loads (비선형 전기부하구성 예측을 위한 최적화 기법 비교 평가)

  • Lee, Soon;Park, Jung-Wook
    • Proceedings of the KIEE Conference
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    • 2007.07a
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    • pp.576-577
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    • 2007
  • 본 논문은 전력시스템 수용가를 구성하는 비선형 부하에 흐르는 왜곡된 파형을 가진 전류의 상대적 비율을 결정하여 비선형 전기부하구성을 예측하기 위한 연구이다. 본 논문에서는 수용가 전기부하 구성 예측을 위한 해결 절차로써 수용가의 수리적 모델링을 통한 시스템 방정식을 도출하였고 최적화 이론을 적용하였다. 또한, 본 시스템에 적용한 최적화 알고리즘으로 steepest descent, conjugate gradient, Broydon-Fletcher-Goldfarb-Shanno (BFGS) 기법을 사용하였고, 예측된 결과들의 성능을 나타내는 지표인 수렴 속도와 정확도 비교를 통하여 분산 전력시스템의 전기부하구성 예측을 위해 BFGS 기법을 적용하는 것이 가장 효율적인 방안임을 보였다.

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Dynamic Embedded Optimization Applied to Power System Stabilizers

  • Sung, Byung Chul;Baek, Seung-Mook;Park, Jung-Wook
    • Journal of Electrical Engineering and Technology
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    • v.9 no.2
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    • pp.390-398
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    • 2014
  • The systematic optimal tuning of power system stabilizers (PSSs) using the dynamic embedded optimization (DEO) technique is described in this paper. A hybrid system model which has the differential-algebraic-impulsive-switched (DAIS) structure is used as a tool for the DEO of PSSs. Two numerical optimization methods, which are the steepest descent and Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithms, are investigated to implement the DEO using the hybrid system model. As well as the gain and time constant of phase lead compensator, the output limits of PSSs with non-smooth nonlinearities are considered as the parameters to be optimized by the DEO. The simulation results show the effectiveness and robustness of the PSSs tuned by the proposed DEO technique on the IEEE 39 bus New England system to mitigate system damping.

Fire Growth of Wood Cribs and Available Safe Egress Time (목재연소시의 실내화재성상과 안전대피시간)

  • 정길순;태순호;이병곤
    • Journal of the Korean Society of Safety
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    • v.8 no.2
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    • pp.72-77
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    • 1993
  • Available Safe Egress Time(ASET) is the time available for occupants to evacuate safely In compartment fire, and It depends on the time of fire detection and hazardous conditions. The purpose of thls study Is to provide an analytical basis and experimental data for estimating the fire growth in compartments and the available safe egress time, and to compare the experimental data with those proposed equations. As a result, hazard order Is poison to CO, descent of smoke layer, poison to $CO_2$, burn to hot smoke layer, and lack of $O_2$, ASET is lengthened in this order. Also, The more fire load is increased, the more ASET is shorted.

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Power System Stabilization using Self Tuning Fuzzy Controller (자기조정 퍼지제어기에 의한 전력계통 안정화에 관한 연구)

  • Chung, H.H.;Chung, D.I.;Joo, S.M.;Koh, H.S.
    • Proceedings of the KIEE Conference
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    • 1994.11a
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    • pp.48-50
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    • 1994
  • In this paper, the optimal fuzzy controller of exciter and governor in synchronous generator improve the stability of power system with varying loads and disturbances in power system. Parameters of the proposed fuzzy controller were optimally self-tuned by the steepest descent method and were applied to power system stabilization. The related simulation results show that the proposed control technique are more powerful than the conventional ones for reductions of undershoot and for minimization of settling time.

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A Study on Steering Control of Autonomous Underwater Vehicle Using Self-Recurrent Wavelet Neural Network (자기 회귀 웨이블릿 신경 회로망을 이용한 자율 수중 운동체의 방향제어에 관한 연구)

  • Kim, Byung-Soo;Park, Sang-Su;Choi, Yoon-Ho;Park, Jin-Bae
    • Proceedings of the KIEE Conference
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    • 2007.07a
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    • pp.1578-1579
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    • 2007
  • In this paper, we propose a new method for designing the steering controller of Autonomous Underwater Vehicle(AUV) using a Self-Recurrent Wavelet Neural Network(SRWNN). The proposed control method is based on a direct adaptive control technique, and a SRWNN is used for the controller of horizontal motion of AUV. A SRWNN is tuned to minimize errors between the SRWNN outputs and the outputs of AUV via the gradient descent(GD) method. Finally, through the computer simulations, we compare the performance of the propose controller with that of the MLP based controller to verify the superiority and effectiveness of the propose controller.

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A Loss-Minimized Power Flow Algorithm Considering Transmission Losses Re-distribution (송전 손실 재분배를 고려한 최소 손실 조류 계산 알고리즘)

  • Chae, Myung-Suk;Lee, Myung-Hwan;Shin, Joong-Rin
    • Proceedings of the KIEE Conference
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    • 1998.11a
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    • pp.223-225
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    • 1998
  • This paper presents a new approach for power flow calculation, which minimizes the transmission losses in power systems with the control of voltage magnitudes on P-V nodes. In this approach, the transmission losses are re-distributed to each P-V node, at each iteration, to reduce the effect of slack. The steepest descent method is adopted, in this study, to minimize the transmission losses augmented with penalty functions to account for voltage constraints. IEEE 14 and 30 buses test systems were used for the performance demonstration of the proposed method in this paper. The simulation results showed that the proposed method can reduce transmission losses and improve voltage profiles of power systems.

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Development of Visual Servo Control System for the Tracking and Grabbing of Moving Object (이동 물체 포착을 위한 비젼 서보 제어 시스템 개발)

  • Choi, G.J.;Cho, W.S.;Ahn, D.S.
    • Journal of Power System Engineering
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    • v.6 no.1
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    • pp.96-101
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    • 2002
  • In this paper, we address the problem of controlling an end-effector to track and grab a moving target using the visual servoing technique. A visual servo mechanism based on the image-based servoing principle, is proposed by using visual feedback to control an end-effector without calibrated robot and camera models. Firstly, we consider the control problem as a nonlinear least squares optimization and update the joint angles through the Taylor Series Expansion. And to track a moving target in real time, the Jacobian estimation scheme(Dynamic Broyden's Method) is used to estimate the combined robot and image Jacobian. Using this algorithm, we can drive the objective function value to a neighborhood of zero. To show the effectiveness of the proposed algorithm, simulation results for a six degree of freedom robot are presented.

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The optimal arrangement of RFID tags for mobile robot's position estimation (이동 로봇의 위치 추정을 위한 RFID Tag의 효율적 배치)

  • Song S.H.;Park H.H.;Moon S.W.;Ji Y.K.;Park J.H.
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2005.10a
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    • pp.901-905
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    • 2005
  • It is very important to arrange landmarks when a mobile robot needs to measure its own location. So, it has been discussed often how to arrange landmarks in the optimal way until now. We, there, chose the RFID (Radio frequency Identification) tags as landmarks which can be observed by a mobile robot, and demonstrated the possibility of the optimal arrangement of them. For this work first, we defined the optimization problem and its parameters for the arrangement of tags. Second, we proposed the algorithm which can be applied to the optimization problem. Finally we could obtain closely optimal and practical arrangement with the minimum number of landmarks which satisfied the necessary condition by experimentation.

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A Trust-Region ICA algorithm (Trust-Region ICA 알고리듬)

  • Park, Heeyoul;Kim, Sookjeong;Park, Seungjin
    • Proceedings of the Korean Information Science Society Conference
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    • 2004.04b
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    • pp.721-723
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    • 2004
  • A trust-region method is a quite attractive optimization technique. It is, in general, faster than the steepest descent method and is free of a learning rate unlike the gradient-based methods. In addition to its convergence property (between linear and quadratic convergence), ifs stability is always guaranteed, in contrast to the Newton's method. In this paper, we present an efficient implementation of the maximum likelihood independent component analysis (ICA) using the trust-region method, which leads to trust-region-based ICA (TR-ICA) algorithms. The useful behavior of our TR-ICA algorithms is confimed through numerical experimental results.

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A Study on Adversarial Attack Using Triplet loss (Triplet Loss를 이용한 Adversarial Attack 연구)

  • Oh, Taek-Wan;Moon, Bong-Kyo
    • Proceedings of the Korea Information Processing Society Conference
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    • 2019.05a
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    • pp.404-407
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    • 2019
  • 최근 많은 영역에 딥러닝이 활용되고 있다. 특히 CNN과 같은 아키텍처는 얼굴인식과 같은 이미지 분류 분야에서 활용된다. 이러한 딥러닝 기술을 완전한 기술로서 활용할 수 있는지에 대한 연구가 이뤄져왔다. 관련 연구로 PGD(Projected Gradient Descent) 공격이 존재한다. 해당 공격을 이용하여 원본 이미지에 노이즈를 더해주게 되면, 수정된 이미지는 전혀 다른 클래스로 분류되게 된다. 본 연구에서 기존의 FGSM(Fast gradient sign method) 공격기법에 Triplet loss를 활용한 Adversarial 공격 모델을 제안 및 구현하였다. 제안된 공격 모델은 간단한 시나리오를 기반으로 검증하였고 해당 결과를 분석하였다.