• 제어로봇시스템학회:학술대회논문집
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• 1988.10b
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• pp.1018-1021
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• 1988

This study is concerned with modeling an elastomer constitutive relation by utilizing the truncated Volterra series. Actual experimental data from the Instron Tester are obtained for combined input, i.e. constant strain rate followed by a constant strain input. These data are then estimated for step inputs and utilized for the truncated Volterra series models. One second order and one third order truncated Volterra series models have been employed to estimated the force-displacement relation which is one of the prominent properities to characterize the viscoelastic material. The third order Volterra series model has better results, compared with those of the second order Volterra series model.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.6
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• pp.71-78
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• 1989

The imput-output relations for nonlinear systems can be explicitly represented by the Volterra series and they can be characterized by the Volterra kernels. This study is concerned with modeling an elastomer force-displacement relation due to step inputs by utilizing the truncated Volterra series. Since it is practically impossible to apply step inputs that have infinite slope at zero time, the loads due to constant penetration(displacement) rate followed by constant penetration inputs are measured as an alternative approach and estimated for step inputs and then utilized for the truncated Volterra series models. One second order and one third order truncated Volterra series models have been employed to model the force-displacement relation which is one of the prominent properties to characterize the viscoelastic material. The third order truncated Volterra series model has better results, compared with those of the second order truncated Volterra series model.

• Journal of the Society of Naval Architects of Korea
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• v.57 no.5
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• pp.305-311
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• 2020

This study presents a probabilistic time series forecast of ship structural response using Bayesian inference combined with Volterra linear model. The structural response of a ship exposed to irregular wave excitation was represented by a linear Volterra model and unknown uncertainties were taken care by probability distribution of time series. To achieve the goal, Volterra series of first order was expanded to a linear combination of Laguerre functions and the probability distribution of Laguerre coefficients is estimated using the prepared data by treating Laguerre coefficients as random variables. In order to check the validity of the proposed methodology, it was applied to a linear oscillator model containing damping uncertainties, and also applied to model test data obtained by segmented hull model of 400,000 DWT VLOC as a practical problem.

• Journal of the Society of Naval Architects of Korea
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• v.51 no.4
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• pp.274-282
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• 2014

Time series of the dynamic response of a slender marine structure was predicted using quadratic Volterra series. The wave-structure interaction system was identified using the NARX(Nonlinear Autoregressive with Exogenous Input) technique, and the network parameters were determined through the supervised training with the prepared datasets. The dataset used for the network training was obtained by carrying out the nonlinear finite element analysis on the freely standing riser under random ocean waves of white noise. The nonlinearities involved in the analysis were both large deformation of the structure under consideration and the quadratic term of relative velocity between the water particle and structure in Morison formula. The linear and quadratic frequency response functions of the given system were extracted using the multi-tone harmonic probing method and the time series of response of the structure was predicted using the quadratic Volterra series. In order to check the applicability of the method, the response of structure under the realistic ocean wave environment with given significant wave height and modal period was predicted and compared with the nonlinear time domain simulation results. It turned out that the predicted time series of the response of structure with quadratic Volterra series successfully captures the slowly varying response with reasonably good accuracy. It is expected that the method can be used in predicting the response of the slender offshore structure exposed to the Morison type load without relying on the computationally expensive time domain analysis, especially for the screening purpose.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.12
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• pp.1173-1177
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• 2015

This paper deals with estimating the acid concentration of pickling process using the Volterra inputs. To estimate the acid concentration, the whole pickling process is represented by the grey box model consists of the white box dealing with known system and the black box dealing with unknown system. Because there is a possibility of nonlinear term in the unknown system, the Volterra series are used to estimate the acid concentration. For the white box modeling, the acid tank solution level and concentration equations are used, and for the black box modeling, the acid concentration is estimated using the Volterra Least Mean Squares (LMS) algorithm and Least Squares (LS) algorithm. The LMS algorithm has the advantage of the simple structure and the low computation, and the LS algorithm has the advantage of lowest error. The simulation results compared to the measured data are included.

• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.1111-1114
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• 2000

In this paper, a method of estimating second-order Volterra model with ARCH errors is presented. Then we use an ECLMS algorithm for noise canceling of nonlinear time series. The validity of the proposed method is demonstrated for estimating second-order Volterra model with ARCH errors, using computer simulations.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.5
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• pp.415-419
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• 2001

This paper proposes and adaptive nonlinear equalizer based on Volterra Series along with M-band wavelet transform(M-DWT). The proposed wavelet transform-domain approach leads to diagonalization of the input vector auto-correlation matrix, which yields clustering its eigenvalue spread around one, and improving the convergence rate of the corresponding transform-domain LMS algorithm. In particular, the proposed adaptive Volterra equalizer is employed to compensate for the output distortion produced by a weakly nonlinear system. Finally, some simulation results obtained by using a TWT amplifier model are provide to demonstrated the converging performance of the proposed approach.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.16-19
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• 1996

The objective of this paper is to present a new adaptive nonlinear compensation method, which is based upon the Pth-order inverse theory and can be implemented in a systematic way, for weakly nonlinear systems that can be modeled by a Volterra series. In particular, employment of the proposed approach for the linearization of a given nonlinear system leads to the effective elimination of (up to a required order) nonlinearities in the overall system output. To demonstrate the feasibility of the proposed method, simulation results using a satellite communication system model are also provided.

• Proceedings of the KIEE Conference
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• 2004.05a
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• pp.3-6
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• 2004

In this paper, the problem of identifying a time-varying nonlinear system in an adaptive way was considered, whereby the time-varying second-order Volterra series was employed to model the system and the filtered weighted least squares (FWLS) algorithm was utilized for the fast parameter tracking capability with low computational burden. Finally, the performance of the proposed approach was demonstrated by providing some computer simulation results.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.49 no.5
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• pp.59-65
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• 2012

In this paper, we investigate the compressed sensing (CS) algorithms for modeling a super-resolution near-field structure (super-RENS) disc system with a sparse Volterra filter. It is well known that the super-RENS disc system has severe nonlinear inter-symbol interference (ISI). A nonlinear system with memory can be well described with the Volterra series. Furthermore, CS can restore sparse or compressed signals from measurements. For these reasons, we employ the CS algorithms to estimate a sparse super-RENS read-out channel. The evaluation results show that the CS algorithms can efficiently construct a sparse Volterra model for the super-RENS read-out channel.