• Transactions on Control, Automation and Systems Engineering
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• 제4권2호
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• pp.109-113
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• 2002

Van de Vusse reactor is known as a highly nonlinear chemical process and has been considered by a number of researchers as a benchmark problem for nonlinear chemical process. Various identification methods for nonlinear system are also verified by applying these methods to Van de Vusse reactor. From the point of view of identification, only the Volterra kernel of second order has been obtained until now. In this paper, the authors show that Volterra kernels of nonlinear Van de Vusse reactor of up to 3rd order are obtained by use of M-sequence correlation method. A pseudo-random M-sequence is applied to Van de Vusse reactor as an input and its output is measured. Taking the crosscorrelation function between the input and the output, we obtain up to 3rd order Volterra kernels, which is the highest order Volterra kernel obtained until now for Van de Vusse reactor. Computer simulations show that when Van de Vusse chemical process is identified by use of up to 3rd order Volterra kernels, a good agreement is observed between the calculated output and the actual output.

• Journal of applied mathematics & informatics
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• 제6권1호
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• pp.175-184
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• 1999

Along with the computation and analysis for nonlinear system being more and more involved in the fields such as automation control electronic technique and electrical power system the nonlin-ear theory has become quite a attractive field for academic research. In this paper we derives the solutions for state equation of nonlinear system by using the inverse operator expression of the so-lutions is obtained. An actual computation example is given giving a comparison between IOM and Runge-kutta method. It has been proved by our investigation that IOM has some distinct advantages over usual approximation methods in that it is computationally con-venient rapidly convergent provides accurate solutions not requiring perturbation linearization or the massive computation inherent in discrietization methods such as finite differences. So the IOM pro-vides an effective method for the solution of nonlinear system is of potential application valuable in nonlinear computation.

• 조명전기설비학회논문지
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• 제12권4호
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• pp.62-69
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• 1998

송변전성비의 비선형영역 운전으로 인하여 발생하는 고조파는 잘 알려져 있지 않으며 이에 대한 연구도 많지 않다. 비선형회로에서 고조파원, 특히 송변전설비의 비선형 운전에 의한 고조파는 근사적으로 비선형 기계진동문 제를 기술하는 Duffing방정식으로 모델링할 수 있다. 본 논문에서는 Duffing방정식을 이용하여 비선형회로에서 고조파 해석올 위한 새로운 해석 기법올 제안하고 기존에 알려진 여러 기법들과 비교하였다. 사례연구를 통하여 제안된 기법과 기존기법을 바교하였으며, 제안된 방법의 활용성을 고찰하였다.

• Smart Structures and Systems
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• 제24권6호
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• pp.683-692
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• 2019

Traditional damage detection methods for nonlinear structures are often based on simplified models, such as the mass-spring-damper and shear-building models, which are insufficient for predicting the vibration responses of a real structure. Conventional global nonlinear finite element model updating methods are computationally intensive and time consuming. Thus, they cannot be applied to practical structures. A decentralized approach for identifying the nonlinear material parameters is proposed in this study. With this technique, a structure is divided into several small zones on the basis of its structural configuration. The unknown material parameters and measured vibration responses are then divided into several subsets accordingly. The structural parameters of each subset are then updated using the vibration responses of the subset with the Newton-successive-over-relaxation (SOR) method. A reinforced concrete and steel frame structure subjected to earthquake loading is used to verify the effectiveness and accuracy of the proposed method. The parameters in the material constitutive model, such as compressive strength, initial tangent stiffness and yielding stress, are identified accurately and efficiently compared with the global nonlinear model updating approach.

• 한국정밀공학회지
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• 제12권5호
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• pp.157-165
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• 1995

In this paper the comparison between the neural networks and traditional approaches as nonlinear system identification methods are considered. Two model structures of neural networks are the state space model and the input output model neural networks. The traditional methods are the AutoRegressive eXogeneous Input model and the Nonlinear AutoRegressive eXogeneous Input model. Computer simulation for an analytic dynamic model of a single input single output nonlinear system has been done for all the chosen models. Model validation for the obtained models also has been done with testing inputs of the sinusoidal, ramp and the noise ramp.

• Journal of applied mathematics & informatics
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• 제30권3_4호
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• pp.395-411
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• 2012

Several methods with order higher than that of Newton methods which are of order 2 have been reported in literature for solving nonlinear equations. The focus of most of these methods was to economize on/minimize the number of function evaluations per iterations. We have demonstrated here that there are several computational pit-falls, such as the violation of fixed-point theorem, that one could encounter while using these methods. Further it was also shown that the overall computational complexity could be more in these high-order methods than that in the second-order Newton method.

• Steel and Composite Structures
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• 제20권4호
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• pp.777-799
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• 2016

One of the major components for performance based seismic design is accurate estimation of critical seismic demand parameters. While nonlinear seismic analysis is the most appropriate analysis method for estimation of seismic demand parameters, this method is very time consuming and complex. Single mode pushover analysis method, N2 method and multi-mode pushover analysis method, modal pushover analysis (MPA) are two nonlinear static methods that have recently been used for seismic performance evaluation of few lateral load-resisting systems. This paper further investigates the applicability of N2 and MPA methods for estimating the seismic demands of ductile unstiffened steel plate shear walls (SPSWs). Three different unstiffened SPSWs (4-, 8-, and 15-storey) designed according to capacity design approach were analysed under artificial and real ground motions for Vancouver. A comparison of seismic response quantities such as, height-wise distribution of floor displacements, storey drifts estimated using N2 and MPA methods with more accurate nonlinear seismic analysis indicates that both N2 and MPA procedures can reasonably estimates the peak top displacements for low-rise SPSW buildings. In addition, MPA procedure provides better predictions of inter-storey drifts for taller SPSW. The MPA procedure has been extended to provide better estimate of base shear of SPSW.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1989년도 한국자동제어학술회의논문집; Seoul, Korea; 27-28 Oct. 1989
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• pp.327-330
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• 1989

Two recent nonlinear control methods of nonlinear geometric method and nonlinear optimal control method are applied to a pH control system with severe nonlinear characteristics. Simulations and experiments show that their performances are very good and robust for various realistic situations such as model parameter mismatches.

• International Journal of Naval Architecture and Ocean Engineering
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• 제3권3호
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• pp.159-173
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• 2011

The two different numerical approaches for solving the nonlinear ship wave problem are discussed in the present paper. One is based on a panel method, which neglects the viscous effects. The other is based on a finite volume method, which take into account the viscous effects by solving RANS equations. Focus is laid upon on the advantages and disadvantages of two methods. The developed methods are applied to calculating the flow around Series 60 hull to validate the performance of the present nonlinear methods. Although the two methods employ quite different numerical approaches, the calculated wave patterns from both methods show good agreements with the experiments. However the potential method simu-lates the global wave pattern accurately, while the viscous method shows better performance for the local wave prediction near a ship.

• Communications for Statistical Applications and Methods
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• 제8권2호
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• pp.565-572
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• 2001

This article explores the problem of ergodicity for the nonlinear autoregressive processes with ARCH structure in a very general setting. A sufficient condition for the geometric ergodicity of the model is developed along the lines of Feigin and Tweedie(1985), thereby extending classical results for specific nonlinear time series. The condition suggested is in turn applied to some specific nonlinear time series illustrating that our results extend those in the literature.