• 제목/요약/키워드: stability function

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A GENERALIZED ADDITIVE-QUARTIC FUNCTIONAL EQUATION AND ITS STABILITY

  • HENGKRAWIT, CHARINTHIP;THANYACHAROEN, ANURK
    • 대한수학회보
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    • 제52권6호
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    • pp.1759-1776
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    • 2015
  • We determine the general solution of the generalized additive-quartic functional equation f(x + 3y) + f(x - 3y) + f(x + 2y) + f(x - 2y) + 22f(x) - 13 [f(x + y) + f(x - y)] + 24f(y) - 12f(2y) = 0 without assuming any regularity conditions on the unknown function f : ${\mathbb{R}}{\rightarrow}{\mathbb{R}}$ and its stability is investigated.

댐핑 영향을 반영하는 Lyapunov 함수 그룹의 유도 및 응용 (Derivation of a Group of Lyapunov Functions reflecting Damping Effects and its Application)

  • 문영현;최병곤;노태훈;이태식;이윤섭
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1995년도 추계학술대회 논문집 학회본부
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    • pp.195-198
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    • 1995
  • Most of the theorems of nonlinear stability is based on the Lyapunov stability theory. The Lyapunov function method is the most well-known and provides precise and rigorous theoretical backgrounds. However, tile conventional approach to direct stability analysis has been performed without taking account of damping effects. For accurate stability analysis of nonlinear systems, it is required to consider the damping effects. This paper presents a new method to derive a group of Lyapunov functions to reflect the damping effects by considering the integral relationships of the system governing equations. This method tan be utilized as a powerful tool to determine the region of attraction.

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Adaptive Neural Network Control for Robot Manipulators

  • Lee, Min-Jung;Choi, Young-Kiu
    • KIEE International Transaction on Systems and Control
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    • 제12D권1호
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    • pp.43-50
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    • 2002
  • In the recent years neural networks have fulfilled the promise of providing model-free learning controllers for nonlinear systems; however, it is very difficult to guarantee the stability and robustness of neural network control systems. This paper proposes an adaptive neural network control for robot manipulators based on the radial basis function netwo.k (RBFN). The RBFN is a branch of the neural networks and is mathematically tractable. So we adopt the RBFN to approximate nonlinear robot dynamics. The RBFN generates control input signals based on the Lyapunov stability that is often used in the conventional control schemes. The saturation function is also chosen as an auxiliary controller to guarantee the stability and robustness of the control system under the external disturbances and modeling uncertainties.

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전압안정도를 고려한 연속선형계획법 기반 최적조류계산 (Voltage Stability Constrained Optimal Power Flow based on Successive Linear Programming)

  • 배승철;신용선;이병준
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2003년도 추계학술대회 논문집 전력기술부문
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    • pp.220-223
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    • 2003
  • This paper presents VSCOPF(Votage Stability Constrained Optimal Power Flow) algorithm based on SLP(Successive Linear Programming) to interpret the large scale system. Voltage stability index used to this paper is L index to be presented by function form. The objective function consists of load shedding cost minimization. Voltage stability indicator constraint was incorporated in traditional OPF formulation. as well as the objective function and constraints are linearlized and the optimal problem is performed by SLP(Successive Linear Programming). In this paper, the effect of voltage stability limit constraint is showed in the optimal load curtailment problems. As a result, an optimal solution is calculated to minimize load shedding cost guaranteeing voltage security level. Numerical examples using IEEE 39-bus system is also presented to illustrate the capabilities of the proposed formulation.

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Control Algorithm of Thyristor Rectifier to Improve Arc Stability in DC Arc Furnace

  • Jung, Kyungsub;Suh, Yongsug;Kim, Taewon;Park, Taejun
    • 전력전자학회:학술대회논문집
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    • 전력전자학회 2012년도 전력전자학술대회 논문집
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    • pp.371-372
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    • 2012
  • In this paper fundamental features of the arc stability in DC arc furnace of 720V/100kA/72MW have been investigated. Cassie-Mayr arc model has been employed for the target dc arc furnace. In order to characterize the parameters of Cassie-Mayr arc model and the behavior of unstable arc dynamics, the advanced arc simulations of magneto-hydrodynamics (MHD) has been performed. Based on the results of MHD simulation, dc arc dynamic resistance is proposed to be an effective arc stability function reflecting the instability of dynamic arc behavior. The experimental result confirms the usefulness of proposed dynamic arc resistance as arc stability function. The proposed arc stability function can be regarded as an effective criterion for the overall power conversion system to maintain highly stable arcing operation leading to better productivity and reliability.

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STABILITY OF TRIGONOMETRIC TYPE FUNCTIONAL EQUATIONS IN RESTRICTED DOMAINS

  • Chung, Jae-Young
    • 한국수학교육학회지시리즈B:순수및응용수학
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    • 제18권3호
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    • pp.231-244
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    • 2011
  • We prove the Hyers-Ulam stability for trigonometric type functional inequalities in restricted domains with time variables. As consequences of the result we obtain asymptotic behaviors of the inequalities and stability of related functional inequalities in almost everywhere sense.

ON THE STABILITY OF A BETA TYPE FUNCTIONAL EQUATIONS

  • Kim, Gwang-Hui;Lee, Young-Whan
    • Journal of applied mathematics & informatics
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    • 제14권1_2호
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    • pp.429-445
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    • 2004
  • In this paper we investigate the generalized Hyers-Ulam-Rassias stability for a functional equation of the form $f(\varphi(x,y)){\;}={\;}\phi(x,y)f(x,y)$, where x, y lie in the set S. As a consequence we obtain stability in the sense of Hyers, Ulam, Rassias, Gavruta, for some well-known equations such as the gamma, beta and G-function type equations.

NFL-FOO에 기준한 SMC의 안정도 증명 : Part 5 (Stability Proof of NFL-FOO-based SMC : Part 5)

  • 이상성;박종근;이주장
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1998년도 하계학술대회 논문집 C
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    • pp.985-987
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    • 1998
  • This paper presents a stability proof for the nonlinear feedback linearization-full order observer-based sliding mode controller (NFL-FOO-based SMC). The closed-loop stability is proved by a Lyapunov function candidate using an addition form of the sliding surface vector and the estimation error.

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