• International journal of advanced smart convergence
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• v.2 no.1
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• pp.12-17
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• 2013

This paper introduces the fuzzy scatter partition-based fuzzy inference system to construct the model for nonlinear process to analyze nonlinear characteristics. The fuzzy rules of fuzzy inference systems are generated by partitioning the input space in the scatter form using Fuzzy C-Means (FCM) clustering algorithm. The premise parameters of the rules are determined by membership matrix by means of FCM clustering algorithm. The consequence part of the rules is represented in the form of polynomial functions and the parameters of the consequence part are estimated by least square errors. The proposed model is evaluated with the performance using the data widely used in nonlinear process. Finally, this paper shows that the proposed model has the good result for high-dimension nonlinear process.

• 전기의세계
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• v.21 no.2
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• pp.25-33
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• 1972

The main focus of this paper is on the study of voltage-current characteristics in disk-type siliconcarbide resistors. For each of the 15 different sintering and other process conditions, 10 samples were prepared. Experiments performed with each sample consist of supplying sinusoidal AC current of a few miliamperes after conditioning-shots with 400ma. Experimental data were examined with regard to the relationship between the process conditions and the nonlinear resistivity. The examination suggests several possibilities of improving the nonlinlinear characteristics of siliconcarbide resistors while maintaining low resitance. One of those possible conditions is to sinter the powdered SiC and the binding materials approximately 2 hours in nitrogen. In addition to describing the nonlinear characteristics of siliconcarbide resistors, this paper also presents the distortion characteristics of current waves vs. the nonlinear exponent, n. Photographical results show that the more nonlinear characteristics samples have, the more distorted current waves are.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.451-454
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• 1998

This paper proposes a new method of Model Predictive Control (MPC) of nonlinear process by us-ing the measured Volterra kernels as the nonlinear model. A nonlinear dynamical process is usually de-scribed as Volterra kernel representation, In the authors' method, a pseudo-random M-sequence is ar plied to the nonlinear process, and its output is measured. Taking the crosscorrelation between the input and output, we obtain the Volterra kernels up to 3rd order which represent the nonlinear characteristics of the process. By using the measured Volterra kernels, we can construct the nonlinear model for MPC. In applying Model Predictive Control to a nonlinear process, the most important thing is, in general, what kind of nonlinear model should be used. The authors used the measured Volterra kernels of up to 3rd order as the process model. The authors have carried out computer simulations and compared the simulation results for the linear model, the nonlinear model up to 2nd Volterra kernel, and the nonlinear model up to 3rd order Vol-terra kernel. The results of computer simulation show that the use of Valterra kernels of up to 3rd order is most effective for Model Predictive Control of nonlinear dynamical processes.

• The Journal of the Korea Contents Association
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• v.11 no.3
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• pp.48-55
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• 2011

In this paper, we analyze the input-output characteristics of fuzzy inference systems according to the division of entire input spaces and the fuzzy reasoning methods to identify the fuzzy model for nonlinear process. And fuzzy model is expressed by identifying the structure and parameters of the system by means of input variables, fuzzy partition of input spaces, and consequence polynomial functions. In the premise part of the rules Min-Max method using the minimum and maximum values of input data set and C-Means clustering algorithm forming input data into the hard clusters are used for identification of fuzzy model and membership function is used as a series of triangular membership function. In the consequence part of the rules fuzzy reasoning is conducted by two types of inferences. The identification of the consequence parameters, namely polynomial coefficients, of the rules are carried out by the standard least square method. And lastly, we use gas furnace process which is widely used in nonlinear process and we evaluate the performance for this nonlinear process.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.11
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• pp.5379-5388
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• 2012

In fuzzy modeling for nonlinear process, the fuzzy rules are typically formed by selection of the input variables, the number of space division and membership functions. The Generation of fuzzy rules for nonlinear processes have the problem that the number of fuzzy rules exponentially increases. To solve this problem, complex nonlinear process can be modeled by generating the fuzzy rules by means of fuzzy division of input space. Therefore, in this paper, rules of non-fuzzy inference systems are generated by partitioning the input space in the scatter form using HCM clustering algorithm. The premise parameters of the rules are determined by membership matrix by means of HCM clustering algorithm. The consequence part of the rules is represented in the form of polynomial functions and the consequence parameters of each rule are identified by the standard least-squares method. And lastly, we evaluate the performance and the nonlinear characteristics using the data widely used in nonlinear process. Through this experiment, we showed that high-dimensional nonlinear systems can be modeled by a very small number of rules.

• Journal of Power System Engineering
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• v.7 no.2
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• pp.44-50
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• 2003

The power steering hose is a kind of high-pressure hose with reinforced braids in rubber material. It is usually manufactured through the swaging process. In this paper, the deformation characteristics of a power steering hose during the swaging process were analyzed using the nonlinear finite element method. The material properties were obtained on experiments, and the contact conditions were used in consideration of real manufacturing process. Investigations were focused on the stress and strain values of the hose and meta] components at the maximum jaw stroke and at the completion of the process. Especially, the results of inner rubber component were interpreted in detail, because of its important role in the hose efficiency.

• International Journal of Automotive Technology
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• v.6 no.5
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• pp.483-489
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• 2005

Based on a two-degree of freedom vehicle model, this paper investigates ride comfort for a heavy off-road vehicle mounted a nonlinear hydropneumatic spring, which is influenced by nonlinear stiffness and damping characteristics of the hydropneumatic spring. Especially, the damping force is derived by applying H. Blasius formula in modeling process according to the real physical structure of the hydropneumatic spring, and the established model of nonlinear stiffness characteristics have been validated by experiments. Furthermore, the effects of parameter variations of the hydropneumatic spring, such as initial charge pressure and damping coefficient, on body acceleration, suspension deflection and dynamic tire deflection are also investigated.

• The Korean Journal of Financial Management
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• v.21 no.1
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• pp.149-181
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• 2004

In this study we perform empirical tests using KOSPI return to investigate the existence of nonlinear characteristics in the generating process of stock returns. There are three categories in empirical tests; the test of nonlinear dependence, nonlinear stochastic process and nonlinear deterministic chaos. According to the analysis of nonlinearity, stock returns are not normally distributed but leptokurtic, and appear to have nonlinear dependence. And it's decided that the nonlinear structure of stock returns can not be completely explained using nonlinear stochastic models of ARCH-type. Nonlinear deterministic chaos system is the feedback system, which the past incidents influence the present, and it is the fractal structure with self-similarity and has the sensitive dependence on initial conditions. To summarize the results of chaos analysis for KOSPI return, it is the persistent time series, which is not IID and has long memory, takes biased random walk, and is estimated to be fractal distribution. Also correlation dimension, as the approximation of fractal dimension, converged stably within 3 and 4, and maximum Lyapunov exponent has positive value. This suggests that chaotic attractor and the sensitive dependence on initial conditions exist in stock returns. These results fit into the characteristics of chaos system. Therefore it's decided that the generating process of stock returns has nonlinear deterministic structure and follow chaotic process.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.401-405
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• 1993

This paper presents a neuro adaptive control method for nonlinear dynamical systems based on artificial neural network systems. The proposed neuro adaptive controller consists of 3 layers artificial neural network system and parallel PD controller. At the early stage in learning or identification process of the system characteristics the PD controller works mainly in order to compensate for the inadequacy of the learning process and then gradually the neuro contrller begins to work instead of the PD controller after the learning process has proceeded. From the simulation studies the neuro adaptive controller is seen to be robust and works effectively for nonlinear dynamical systems from a practical applicational points of view.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.15 no.1
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• pp.50-60
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• 2016

Laminate composites have a number of excellent characteristics in aspects of strength, stiffness, bending, and buckling. Buckling and postbuckling analysis of laminate composites with layups of [90/0]2s, $[{\pm}45/90/0]s$, $[{\pm}45]2s$ has been carried using the Total Lagrangian nonlinear Newton-Raphson method. The formulation of a geometrically nonlinear composite shell element based on a nonlinear large deformation method is presented. The used element is an eight-node degenerated shell element with six degrees of freedom. Square, circular cylinder, and arch panel laminate geometries were analyzed to verify the effects of the layups on the buckling and postbuckling behavior. The results showed that the effects of laminate layups on bucking and postbuckling behavior and the present formulation showed very good agreement with existing references.