• Journal of Theoretical and Applied Mechanics
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• v.3 no.1
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• pp.66-80
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• 2002

The bilinear formulation proposed earlier by Peters and Izadpanah to develop finite elements in time to solve undamped linear systems, Is extended (and found to be readily amenable) to develop time finite elements to obtain transient responses of both linear and nonlinear, and damped and undamped systems. The formulation Is used in the h-, p- and hp-versions. The resulting linear and nonlinear algebraic equations are differentiated to obtain the first- and second-order sensitivities of the transient response with respect to various system parameters. The present developments were tested on a series of linear and nonlinear examples and were found to yield, when compared with results obtained using other methods, excellent results for both the transient response and Its sensitivity to system parameters. Mostly. the results were obtained using the Legendre polynomials as basis functions, though. in some cases other orthogonal polynomials namely. the Hermite. the Chebyshev, and integrated Legendre polynomials were also employed (but to no great advantage). A key advantage of the time finite element method, and the one often overlooked in its past applications, is the ease In which the sensitivity of the transient response with respect to various system parameters can be obtained. The results of sensitivity analysis can be used for approximate schemes for efficient solution of design optimization problems. Also. the results can be applied to gradient-based parameter identification schemes.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.250-253
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• 1998

This paper presents a multi-modal neural network composed of a preprocessing module and a multi-layer neural network module in order to enhance the nonlinear characteristics of neural network. The former module is based on spectral method using Chebyschev polynomials and transforms input data into spectra. The latter module identifies the system using the spectra generated by the preprocessing module. The omnibus numerical experiments show that the method is applicable to many a nonlinear dynamic system in the real world, and that preprocessing using Chebyschev polynomials reduces the number of neurons required for the multi-layer neural network.

• Journal of Power Electronics
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• v.19 no.3
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• pp.771-783
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• 2019

Due to nonlinear-synthetic uncertainty including the total unknown nonlinear load torque, the total parameter variation and the fixed load torque, a synchronous reluctance motor (SynRM) driving a continuously variable transmission (CVT) system causes a lot of nonlinear effects. Linear control methods make it hard to achieve good control performance. To increase the control performance and reduce the influence of nonlinear time-synthetic uncertainty, an admixed recurrent Gegenbauer orthogonal polynomials neural network (ARGOPNN) with a modified particle swarm optimization (MPSO) control system is proposed to achieve better control performance. The ARGOPNN with a MPSO control system is composed of an observer controller, a recurrent Gegenbauer orthogonal polynomial neural network (RGOPNN) controller and a remunerated controller. To insure the stability of the control system, the RGOPNN controller with an adaptive law and the remunerated controller with a reckoned law are derived according to the Lyapunov stability theorem. In addition, the two learning rates of the weights in the RGOPNN are regulating by using the MPSO algorithm to enhance convergence. Finally, three types of experimental results with comparative studies are presented to confirm the usefulness of the proposed ARGOPNN with a MPSO control system.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.52.2-52
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• 2002

In this paper we consider an approach to a formal linearization for time-variant nonlinear systems. A time-variant nonlinear sysetm is assumed to be described by a time-variant nonlinear differential equation. For this system, we introduce a coordinate transformation function which is composed of the Chebyshev polynomials. Using Chebyshev expansion to the state variable and Laguerre expansion to the time variable, the time-variant nonlinear sysetm is transformed into the time-variant linear one with respect to the above transformation function. As an application, we synthesize a time-variant nonlinear observer. Numerical experiments are included to demonstrate the validity of...

• Journal of the Korean Mathematical Society
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• v.52 no.5
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• pp.1069-1096
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• 2015

In this article we introduce a numerical method, named Gegenbauer wavelets method, which is derived from conventional Gegenbauer polynomials, for solving fractional initial and boundary value problems. The operational matrices are derived and utilized to reduce the linear fractional differential equation to a system of algebraic equations. We perform the convergence analysis for the Gegenbauer wavelets method. We also combine Gegenbauer wavelets operational matrix method with quasilinearization technique for solving fractional nonlinear differential equation. Quasilinearization technique is used to discretize the nonlinear fractional ordinary differential equation and then the Gegenbauer wavelet method is applied to discretized fractional ordinary differential equations. In each iteration of quasilinearization technique, solution is updated by the Gegenbauer wavelet method. Numerical examples are provided to illustrate the efficiency and accuracy of the methods.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2006.04a
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• pp.623-630
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• 2006

In this paper, a geometric nonlinear analysis procedure of beam-column element including multi-noded cable element is presented. For this, first a stiffness matrix about beam-column element which considers the second effect of initial force supposing the curved shape at each time step with Hermitian polynomials as the shape function is derived and second, tangent stiffness matrix about multi-noded cable element being too. To verify geometric nonlinearity of this newly developed multi-noded cable-truss element, IPS(Innovative Prestressed Support) system using this theory is analysed by geometric nonlinear method and the results are compared with those by linear analysis.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.2
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• pp.190-194
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• 2004

This paper shows the application of fuzzy system for a modeling of nonlinear biochemical process. A wastewater treatment process for nitrogen removal in a sequencing batch reactor (SBR) is presented and fuzzy systems with different consequent polynomials in the fuzzy rules to model and identify the oxidation reduction potential (ORP) of the process are introduced. The paper compares, analyzes the results of fuzzy modeling, and shows the nonlinear process can be modeled reasonably well by the present scheme.

• Journal for History of Mathematics
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• v.26 no.2_3
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• pp.149-161
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• 2013

The history of finding solutions of linear equations went back to some thousand years ago, and has been steadily developed to solve systems of higher degree polynomials. The method to eliminate variables came into use around the 17th and 18th century. This technique has been extended to the resultant theory that was laid in the 19th century by outstanding mathematicians as Euler, Sylvester, and B$\acute{e}$zout. In this paper we discuss the historical reflection about the development of solving system of polynomials. We add a special emphasis on E. B$\acute{e}$zout who gave the first account on the resultant which is a generalization of discriminant and Gauss elimination method.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.2
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• pp.277-284
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• 2018

In this paper, a new numerical method of finding the roots of a nonlinear system is proposed, which extends the conventional fixed point iterative method by relaxing the constraints on it. The proposed method determines the real valued roots and expands the convergence region by relaxing the constraints on the conventional fixed point iterative method, which transforms the diverging root searching iterations into the converging iterations by employing the metric induced by the geometrical characteristics of a polynomial. A metric is set to measure the distance between a point of a real-valued function and its corresponding image point of its inverse function. The proposed scheme provides the convenience in finding not only the real roots of polynomials but also the roots of the nonlinear systems in the various application areas of science and engineering.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.173-174
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• 2006

High power amplifier (HPA), which is used in transmitter of wireless communication systems, usually works in near saturation point in order to achieve maximum efficiency. In this region, HPA can introduce undesirable nonlinear effects. In this paper, we present a polynomial modeling method for efficient techniques to compensate for nonlinear distortion introduced by nonlinear HPA. Proposed polynomial predistorter inverses actual amplifier. Namely, we derive polynomials of amplifiers from analytical method and the electrical parameters in the data sheet of an actual amplifier and then can derive polynomial predistorter by inversing them. It is an effective and a simple method to compensate nonlinear distortion. SSPA(Solid-state power amplifier) is considered. We also analyze the effects of predistortion on the SER performance of communication system with 16-QAM modulation format. The results have shown the efficiency of this model.