• Journal of Institute of Control, Robotics and Systems
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• v.18 no.3
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• pp.218-223
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• 2012

Maintenance and improvement of the graph connectivity is very important for decentralized multi-agent systems. Although the CBBA (Consensus-Based Bundle Algorithm) guarantees suboptimal performance and bounded convergence time, it is only valid for connected graphs. In this study, we apply a decentralized estimation procedure that allows each agent to track the algebraic connectivity of a time-varying graph. Based on this estimation, we design a decentralized gradient controller to maintain the graph connectivity while agents are traveling to perform assigned tasks. Simulation result for fully-actuated first-order agents that move in a 2-D plane are presented.

• Journal of international Conference on Electrical Machines and Systems
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• v.1 no.1
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• pp.114-120
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• 2012

Eco-driving technique for electric vehicles (EVs) is investigated in this paper. Many findings on EVs have been reported; however, they did not deal with eco-driving from the viewpoint of theoretical study. The authors have developed an energy-saving driving technique - the so-called "eco-driving" technique based on dynamic programming (DP). Optimal speed profile of an EV, which minimizes the amount of total energy consumption, was determined under fixed origin and destination, running time, and track conditions. DP algorithm can deal with such complicated conditions and can also derive the optimal solution. Using the proposed method, simulations were run for some cases. In particular, the author ran simulations for the case of a gradient road with a traffic signal. The optimization model was solved with MATLAB.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2002.04a
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• pp.335-342
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• 2002

A continuum-based design sensitivity analysis (DSA) method fur non-shape problems is developed for geometrically nonlinear elastic structures. The non-shape problem is characterized by the design variables that are not associated with the domain of system like sizing, material property, loading, and so on. Total Lagrangian formulation with the Green-Lagrange strain and the second Piola-Kirchhoff stress is employed to describe the geometrically nonlinear structures. The spatial domain is discretized using the 4-node isoparametric plane stress/strain elements. The resulting nonlinear system is solved using the Newton-Raphson iterative method. To take advantage of the derived analytical sensitivity In topology optimization, a fast and efficient design sensitivity analysis method, adjoint variable method, is employed and the material property of each element is selected as non-shape design variable. Combining the design sensitivity analysis method and a gradient-based design optimization algorithm, an automated design optimization method is developed. The comparison of the analytical sensitivity with the finite difference results shows excellent agreement. Also application to the topology design optimization problem suggests a very good insight for the layout design.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.8
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• pp.1004-1013
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• 1999

This paper considers the transient stability problem of power system. The power system model is given as interconnected system consisting of many machines which are described by swing equations. We design a transient stability controller using passivity and neural network. The structure of the neural network controller is derived using a filtered error/passivity approach. In general, a neural network cannot be guaranteed to be passive, but the weight tuning algorithm given here do guarantee desirable passivity properties of the neural network and hence of the closed-loop error system. Moreover proposed controller shows good robustness by simulation for uncertainties in parameters, which can not be shown in the speed gradient method proposed by Fradkov[3,7].

• Annual Conference of KIPS
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• 2006.11a
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• pp.3-6
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• 2006

멀티레벨의 feed-forward 네트워크에 대한 학습 방법은 기울기 방법과 전역 최적화방법으로 나눌 수 있다. 역전파 또는 그 변형적인 방법들과 같은 기울기 하강 방법은 편리하기 때문에 여러 분야에서 다양하게 사용되고 있다. 하지만, 역전파와 관련된 가장 큰 문제는 지역 최소점에 빠진다는 것이다. 따라서 본 논문에서 기울기 하강 방법의 단순성을 침범하지 않고 지역 최소점을 극복할 수 있는 개선된 기울기 하강 방법을 제안한다. 제안하는 방법은 상위 연결과 하위연결을 분리하여 훈련하고 평가하기 때문에 이원적인 기울기 하강 방법이라 칭한다. 그렇기 때문에, 은닉층 유닛의 목표 값들은 하위 연결의 평가 툴로써 사용한다. 논문에서 제안하는 방법의 성능은 다양한 실험을 통해서 검증된다.

• Journal of Information Processing Systems
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• v.16 no.1
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• pp.145-154
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• 2020

Maximum likelihood (ML) is the best estimator asymptotically as the number of training samples approaches infinity. This paper deduces an adaptive algorithm for blind signal processing problem based on gradient optimization criterion. A parametric density model is introduced through a parameterized generalized distribution family in ML framework. After specifying a limited number of parameters, the density of specific original signal can be approximated automatically by the constructed density function. Consequently, signal separation can be conducted without any prior information about the probability density of the desired original signal. Simulations on classical biomedical signals confirm the performance of the deduced technique.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.4
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• pp.696-705
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• 1997

This paper presents an efficient adaptive predistortion technique compensating linear and nonlinear distortions caused by high-power amplifier (HPA) with memory in OFDM systems. The efficient adaptive data predistortion techniques proposed for compensation of HPA with memory in single carrier systems cannot be applied to OFDM systems since the possible input levels for HPA is infinite in OFDM systems. Also, previous adaptive predistortion techniques, based on Volterra series modeling, are not suitable for real-time implementation due to high computational burden and slow convergence rate. In the proposed approach, the memoryless HPA preceded by a linear filter in OFDM systems is modeled by the Wiener system which is then precompensated by the proposed adaptive predistorter with a minimum number of filter taps. An adaptive algorithm for adjusting the proposed adaptive predistorter is derived using the stochastic gradient method. It is demonstrated by computer simulation that the performance of OFDM system suffering from nonlinear distortion can be greatly improved by the proposed efficient adaptive predistorter using a small number of filter taps.

• Nuclear Engineering and Technology
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• v.30 no.6
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• pp.496-506
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• 1998

This paper deals with the computational modeling of buoyancy-driven turbulent heat transfer involving spatially uniform volumetric heat sources in semicircular geometry. The Launder & Sharma low-Reynolds number k-$\varepsilon$ turbulence model without any modifications and the SIMPLER computational algorithm were used for the numerical modeling, which was incorporated into the new computer code CORE-TNC. This computer code was subsequently benchmarked with the Mini-ACOPO experimental data in the modified Rayleigh number range of 2$\times$10$^{13}$ $\times$10$^{14}$ . The general trends of the velocity and temperature fields were well predicted by the model used, and the calculated isotherm patterns were found to be very similiar to those observed in previous experimental investigations. The deviation between the Mini-ACOPO experimental data and the corresponding numerical results obtained with CORE-TNC for the average Nusselt number was less than 30% using fine grid in the near-wall region and the three-point difference formula for the wall temperature gradient. With isothermal pool boundaries, heat was convected predominantly to the upper and adjacent lateral surfaces, and the bottom surface received smaller heat fluxes.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.19 no.1
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• pp.71-78
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• 1983

A method is given for obtaining low-order models for a linear time-invariant system of high-order by minimizing a functional of the reduction error between the output response of the original system and the low-order model. The method is based on the Astrom's algorithm for the evaluation of complex integrals and the conjugate gradient method of Fletcher-Reeves. An example illustrating the application of this method is given for approximation of a 4-th order system to be used in the load frequency control of generator systems.

• 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.