• 전기학회논문지
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• 제58권12호
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• pp.2311-2315
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• 2009

This paper presents a method to apply energy margin for assesment of total transfer capability (TTC). In order to calculate energy margin, two values of the transient energy function have to be computed. The first value is transient energy that is the sum of kinetic and potential energy at the end of fault. The second is critical energy that is potential energy at controlling UEP(Unstable Equilibrium Point). It is seen that TTC level is determined by not only bus voltage magnitudes and line thermal limits but also transient stability. TTC assessment is compared by the repeated power flow(RPF) method and optimization method.

• Journal of applied mathematics & informatics
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• 제27권5_6호
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• pp.1411-1427
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• 2009

We propose a model based on Lotka-Volterra dynamics with two competing spices which are affected not only by harvesting but also by the presence of a predator, the third species. Hyperbolic and linear response functions are considered. We derive the conditions for global stability of the system using Lyapunov function. The optimal harvest policy is studied and the solution is derived in the interior equilibrium case using Pontryagin's maximal principle. Finally, some numerical examples are discussed. The nature of variations in the two prey species and one predator species is studied extensively through graphical illustrations.

• Journal of Power Electronics
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• 제7권1호
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• pp.1-12
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• 2007

Novel nonlinear backstepping control with integrated adaptive control function is developed for high-performance positioning control systems. The proposed schemes are synthesized by a systematic approach and implemented based on a modern low-cost DSP controller, TMS320C32. A baseline backstepping control scheme is derived first, and is then extended to include a nonlinear adaptive control against the system parameter changes and load variations. The backstepping control utilizes Lyapunov function to guarantee the convergence of the position tracking error. The final control algorithm is a convenient in the implementation of a practical 32-bit DSP controller. The new control system can achieve superior performance over the conventional nested PI controllers, with improved position tracking, control bandwidth, and robustness against external disturbances, which is demonstrated by experimental results.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 춘계 학술대회 학술발표 논문집
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• pp.329-332
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• 2003

본 논문에서는 새로이 제안된 자기 구조화하는(Self-structuring) 새로운 Radial-Basis Function Network(RBFN)에 대해서 실험적인 검증을 했다. 이 자기 구조화하는 새로운 RBFN은 기존의 RBFN과 비교해서 여러 장점이 있다. Lyapunov 이론에 기초해서 새로운 학습 규칙을 선정하였기 때문에 시스템의 안정도를 보장할 수 있다. 그리고, 자기 구조화의 과정 즉, 생성과 병합을 통해 은닉층에서 적정수의 뉴런을 결정할 수 있다. 기존의 RBFN과 성능을 비교하기 위하여, 실제 비선형 시스템인 2축 암로봇에 대해 실험한 결과를 보였다. 결과적으로, 우리는 실험결과를 통해 자기 구조화하는 RBFN의 효율적인 구조와 시스템에 대한 안정도를 보장함을 볼 수 있다.

• International Journal of Automotive Technology
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• 제8권1호
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• pp.33-38
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• 2007

Since it is difficult to analytically express the Melnikov function when a dynamic system possesses multiple saddle fixed points with homoclinic and/or heteroclinic orbits, this paper investigates a vehicle model with nonlinear suspension spring and hysteretic damping element, which exhibits multiple heteroclinic orbits in the unperturbed system. First, an algorithm for Melnikov integrals is developed based on the Melnikov method. And then the amplitude threshold of road excitation at the onset of chaos is determined. By numerical simulation, the existence of chaos in the present system is verified via time history curves, phase portrait plots and $Poincar{\acute{e}}$ maps. Finally, in order to further identify the chaotic motion of the nonlinear system, the maximal Lyapunov exponent is also adopted. The results indicate that the numerical method of estimating chaotic threshold is an effective one to complicated vehicle systems.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.331-331
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• 2000

This paper presents the mixed $H_2/H_{\infty}$ output feedback controIler design method for linear systems with delayed state. The objective is to design the output feedback controller which minimizes the H$_2$-norm of one transfer function while ensuring the H$_{\infty}$-norm of the other is held below a chosen level. When objective is tormulated in terms of a common Lyapunov function, the sufficient conditions of existence of mixed $H_2/H_{\infty}$ controller are given in terms of LMIs. terms of LMIs.

• 전자공학회논문지B
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• 제33B권7호
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• pp.32-39
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• 1996

In this paper, we describe the algorithm which controls an unknown nonlinear system with multilayer neural network. The multilayer neural netowrk can be used to approximate any continuous function to any desired degree of accuracy. With the former fact, we approximate unknown nonlinear function on the nonlinear system by using of multilayer neural netowrk. The weights on the hidden layer of multilayer neural network are updated by gradient method. The weight-update rule on the output layer is derived to satisfy lyapunov stability. Also, we obtain secondary controller form deriving step. The global control system consists of controller using feedback linearization method and secondary controller is order to satisfy layapunov stability. The proposed control algorithm is verified through computer simulation.

• 대한전기학회논문지:시스템및제어부문D
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• 제52권7호
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• pp.418-423
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• 2003

In order to describe the upper bound of the uncertainties without any information of the structure, we assume that the upper bound is represented as a Fredholm integral equation of the first kind, that is, an integral of the product of a predefined kernel with an unknown influence function. Based on the improved Lyapunov function, we propose an adaptation law that is capable of estimating the upper bound and we design a sliding mode control, which controls effectively for uncertain dynamic systems.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 D
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• pp.2283-2286
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• 2000

Sliding control is a powerful approach to controlling nonlinear and uncertain systems. Conventional sliding mode control suffer' from high control gain and chattering problem. also it needs mathematic! modeling equations for control systems. A Fuzzy controller is endowed with control rules and membership function that are constructed on the knowledge of expert, as like intuition and experience. but It is very difficult to obtain the exact values which are the membership function and consequent parameters. In this paper, without mathematical modeling equations, the plant parameters in sliding mode are estimated by the indirect adaptive fuzzy method. the proposed algorithm could analyze the system's stability and convergence behavior using Lyapunov theory. so sliding modes are reconstructed and decreased tracking error. moreover convergence time took a short. An example of inverted pendulum is given for demonstration of the robustness of proposed methodology.

• 대한전기학회논문지:시스템및제어부문D
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• 제50권1호
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• pp.38-44
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• 2001

This paper investigates the direct adaptive control of nonlinear systems using RBFN(radial basis function networks). The structure of the controller consists of a fixed PD controller and a RBFN controller in parallel. An adaptation law for the parameters of RBFN is developed based on the Lyapunov stability theory to guarantee the stability of the overall control system. The filtered tracking error between the system output and the desired output is shown to be UUB(uniformly ultimately bounded). To evaluate the performance of the controller, the proposed method is applied to the trajectory contro of the two-link manipulator.