• 한국강구조학회 논문집
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• 제21권6호
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• pp.563-574
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• 2009

본 논문은 기하학적 비선형성을 가진 보존적 단일 하중 매개변수의 탄성 상태 공간구조의 탄성 분기 좌굴이론에 관한 수치 해석적 기본 방법 및 경로 추적, pin-pointing, 경로 전환을 기술하고 있다. 비선형 탄성 불안정 상태는 극한점과 분기점으로 분류될 수 있으며, 평형경로상의 평형점의 계산 및 평형경로상의 특이점을 찾기 위한 pin-pointing 반복계산을 수행하는 일반적인 비선형 수치해석법으로 극한점을 계산할 수 있다. 그러나 분기좌굴 해석을 위해서는 좌굴 후 분기경로의 추적을 위한 분기경로 전환 알고리즘이 추가적으로 필요하다. 본문에서는 에너지이론에 기초한 일반 탄성안정이론을 소개하고, 평형경로 추적, 다분기 좌굴점을 찾기 위한 간접법과 다분기의 경로 전환에 관한 이론을 전개한다. 분기좌굴 해석예제로 트러스로 이루어진 스타돔, 핀지지의 평면아치의 분기좌굴 해석을 수행하여 본문에서 제시한 수치해석법의 정확성 및 적용성을 검증한다.

• Journal of Power Electronics
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• 제9권1호
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• pp.61-67
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• 2009

In this paper, a simple technique is presented for robust stability testing of perturbed DC-DC converters having multi-linear uncertainty structure. This technique provides a necessary and sufficient condition for testing robust stability. It is based on the corollary of Routh criterion and gridding of parameters. The previous work based on parametric control theory using Kharitonov's theorem and Hermite Biehler theorem gives conservative results and only the sufficient condition of stability, whereas the proposed method provides the necessary and sufficient condition for testing robust stability and it is computationally efficient. The superiority of the method is compared with the Edge theorem.

• International Journal of Control, Automation, and Systems
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• 제6권1호
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• pp.24-34
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• 2008

A novel neural network model, termed the standard neural network model (SNNM), similar to the nominal model in linear robust control theory, is suggested to facilitate the synthesis of controllers for delayed (or non-delayed) nonlinear systems composed of neural networks. The model is composed of a linear dynamic system and a bounded static delayed (or non-delayed) nonlinear operator. Based on the global asymptotic stability analysis of SNNMs, Static state-feedback controller and dynamic output feedback controller are designed for the SNNMs to stabilize the closed-loop systems, respectively. The control design equations are shown to be a set of linear matrix inequalities (LMIs) which can be easily solved by various convex optimization algorithms to determine the control signals. Most neural-network-based nonlinear systems with time delays or without time delays can be transformed into the SNNMs for controller synthesis in a unified way. Two application examples are given where the SNNMs are employed to synthesize the feedback stabilizing controllers for an SISO nonlinear system modeled by the neural network, and for a chaotic neural network, respectively. Through these examples, it is demonstrated that the SNNM not only makes controller synthesis of neural-network-based systems much easier, but also provides a new approach to the synthesis of the controllers for the other type of nonlinear systems.

• 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.362-367
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• 1996

In this paper, the eigenstructure of a class of linear time varying systems, termed as linear quasi-time invariant(LQTI) systems, is investigated. A system composed of dynamic devices such as linear time varying capacitors and resistors can be an example of the class. To effectively describe and analyze the LQTI systems, a generalized differential operator G is introduced. Then the dynamic systems described by the operator G are studied in terms of eigenvalue, frequency characteristics, stability and an extended convolution. Some basic attributes of the operator G are compared with those of the differential operator D. Also the corresponding generalized Laplace transform pair is defined and relevant properties are derived for frequency domain analysis of the systems under consideration. As an application example, a LQTI circuit is examined by using the concept of eigenstructure of LQTI system. The LQTI filter processes the sinusoidal signals modulated by some functions.

• 대한수학회지
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• 제45권3호
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• pp.871-881
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• 2008

In this paper, we study the core stability of the dominating set game which has arisen from the cost allocation problem related to domination problem on graphs. Let G be a graph whose neighborhood matrix is balanced. Applying duality theory of linear programming and graph theory, we prove that the dominating set game corresponding to G has the stable core if and only if every vertex belongs to a maximum 2-packing in G. We also show that for dominating set games corresponding to G, the core is stable if it is large, the game is extendable, or the game is exact. In fact, the core being large, the game being extendable and the game being exact are shown to be equivalent.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2003년도 추계학술대회
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• pp.219-226
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• 2003

In this paper, it is presented a new scheme of adaptive-neuro control system to implement real-time control of robot manipulator. Unlike the well-established theory fir the adaptive control of linear systems, there exists relatively little general theory fir the adaptive control of nonlinear systems. Adaptive control technique is essential fir providing a stable and robust performance fir application of robot control. The proposed neuro control algorithm is one of teaming a model based error back-propagation scheme using Lyapunov stability analysis method. Through simulation, the proposed adaptive-neuro control scheme is proved to be a efficient control technique f3r real-time control of robot system using DSPs.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2003년도 춘계학술대회 논문집
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• pp.305-311
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• 2003

We propose a new technique of adaptive-neuro controller design to implement real-time control of robot manipulator, Unlike the well-established theory for the adaptive control of linear systems, there exists relatively little general theory for the adaptive control of nonlinear systems. Adaptive control technique is essential for providing a stable and robust performance for application of robot control. The proposed neuro control algorithm is one of loaming a model based error back-propagation scheme using Lyapunov stability analysis method. Through simulation, the proposed adaptive-neuro control scheme is proved to be a efficient control technique for real time control of robot system using DSPs(TMS320C50)

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2004년도 추계학술대회 논문집
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• pp.193-200
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• 2004

In this paper, it is presented a new scheme of adaptive-neuro control system to implement real-time control of robot manipulator. Unlike the well-established theory for the adaptive control of linear systems, there exists relatively little general theory for the adaptive control of nonlinear systems. Adaptive control technique is essential for providing a stable and robust performance for application of robot control. The proposed neuro control algorithm is one of learning a model based error back-propagation scheme using Lyapunov stability analysis method. Through simulation, the proposed adaptive-neuro control scheme is proved to be a efficient control technique for real-time control of robot system using DSPs.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 하계학술대회 논문집 A
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• pp.112-115
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• 2001

Eigenvalue perturbation theory of augmented system matrix(AMEP) is a useful tool in the analysis and design of large scale power systems. This paper describes the application results of AMEP algorithm with respect to all controller parameter of KEPCO systems. AMEP for interarea and local mode can be used for turning controller parameter, and verifying system data and linear model of controller.

• 설비공학논문집
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• 제15권2호
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• pp.126-131
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• 2003

Convective instability driven by surface tension is analyzed in an initially quiescent water absorbing ammonia gas with heat transfer using the linear stability analysis. The propagation theory is adapted to find the critical conditions of the onset of Marangoni convection. In this theory, the solutal penetration depth is chosen as the length scale factor. The results show that the liquid layer becomes more stable with decreasing the Schmidt number and increasing the Lewis number. It is also found that there is a critical Biot number to make the liquid layer be most unstable, and there is a linear relationship between the thor-mal Marangoni number and the solutal Marangoni number.