Identification of nonlinear systems using a piecewise-linear Hammerstein model

Dolanč, Gregor; Strmĉnik, Stanko

doi:10.1016/j.sysconle.2004.08.002

Cited by 55 publications

(35 citation statements)

References 15 publications

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“…Therefore, the identification of nonlinear dynamic systems using Hammerstein and Wiener models has been an active research area for many years. Some recent works dealing with the Hammerstein models can be found in [1][2][3][4][5][6][7][8][9][10][11][12], while the Wiener models are used in e.g. [13][14][15][16][17][18][19][20][21][22].…”

Section: Introductionmentioning

confidence: 99%

Identification of nonlinear dynamic systems with input saturation and output backlash using three-block cascade models

Vörös

2014

Journal of the Franklin Institute

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Section: Introductionmentioning

confidence: 99%

Identification of nonlinear dynamic systems with input saturation and output backlash using three-block cascade models

Vörös

2014

Journal of the Franklin Institute

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“…The first step consists in 8 If time is discrete, the symbol is replaced by . 9 under the condition that the convergence properties of the algorithm do not change if the identification input is multiplied by a nonzero constant.…”

Section: Resultsmentioning

confidence: 99%

“…In [6] a discretetime Wiener system with a special class of nonlinearities is considered. In [9] a discrete-time Hammerstein system with a special class of nonlinearities is considered. Other references include [10,17,19,22,7].…”

Section: Introductionmentioning

confidence: 99%

A Unified Approach for the Identification of SISO/MIMO Wiener and Hammerstein Systems*

Ikhouane

Giri

2012

IFAC Proceedings Volumes

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Hammerstein and Wiener models are nonlinear representations of systems composed by the coupling of a static nonlinearity N and a linear system L in the form N-L and L-N respectively. These models can represent real processes which made them popular in the last decades. The problem of identifying the static nonlinearity and linear system is not a trivial task, and has attracted a lot of research interest. It has been studied in the available literature either for Hammerstein or Wiener systems, and either in a discrete-time or continuous-time setting. The objective of this paper is to present a unified framework for the identification of these systems that is valid for SISO and MIMO systems, discrete and continuous-time setting, and with the only a priori knowledge that the system is either Wiener or Hammerstein.

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“…It is assumed that the constants d, r and s are known. Assuming b 0 = 1 (one parameter can always be fixed in this model), the internal variable x(·) can be separated in the linear block description as follows (11) and substitution of (7) only for the separated variable x(t-d) leads to the following equation…”

Section: Cascade Systems With Input Backlashmentioning

confidence: 99%

Identification of Nonlinear Cascade Systems with Time-Varying Backlash

Vörös¹

2011

Journal of Electrical Engineering

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Recursive identification of cascade systems with time-varying input backlash and linear dynamic system is presented. A new analytic form of backlash characteristic description is used, hence all the parameters in the cascade model equation are separated and their estimation is solved as a quasi-linear problem using the recursive least squares method with internal variable estimation. Simulation studies are included.K e y w o r d s: nonlinear systems, backlash, cascade systems, recursive identification, time-varying systems

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Identification of nonlinear systems using a piecewise-linear Hammerstein model

Cited by 55 publications

References 15 publications

Identification of nonlinear dynamic systems with input saturation and output backlash using three-block cascade models

Identification of nonlinear dynamic systems with input saturation and output backlash using three-block cascade models

A Unified Approach for the Identification of SISO/MIMO Wiener and Hammerstein Systems*

Identification of Nonlinear Cascade Systems with Time-Varying Backlash

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