2011
DOI: 10.2478/v10187-011-0014-2
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Identification of Nonlinear Cascade Systems with Time-Varying Backlash

Abstract: 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-va… Show more

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Cited by 18 publications
(10 citation statements)
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“…By the iterative technique, Liu and Bai [15] discussed a least squares estimation algorithm for a Hammerstein system. Based on the key term separation principle, Vörös [16], [17] studied an appropriate switching function to model Hammerstein systems with multisegment piecewiselinear characteristics and with backlash nonlinearity. Using the hierarchical identification principle, Wang et al [18] presented a hierarchical least squares algorithm for a Hammerstein state space system.…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation
“…By the iterative technique, Liu and Bai [15] discussed a least squares estimation algorithm for a Hammerstein system. Based on the key term separation principle, Vörös [16], [17] studied an appropriate switching function to model Hammerstein systems with multisegment piecewiselinear characteristics and with backlash nonlinearity. Using the hierarchical identification principle, Wang et al [18] presented a hierarchical least squares algorithm for a Hammerstein state space system.…”
Section: Introductionmentioning
confidence: 99%
“…2) Based on the polynomial transformation technique and the key term separation principle [16], [17], this brief transforms the Hammerstein CARMA system into a linear dual-rate identification model, i.e., the output is linear about only one parameter vector, and presents a key term separation based least squares algorithm to estimate the parameter vector of the linear dual-rate model. The two proposed methods possess higher computational efficiency compared with the previous over-parameterization least squares method [21], which needs to compute the redundant parameter products between the parameters of the nonlinear block and the linear block, and separate parameters from their products.…”
Section: Introductionmentioning
confidence: 99%
“…In previous applications, Hammerstein systems with a two-segment piecewise-linear nonlinearity have been studied in [12], and an extension to a discontinuous two-segment piecewise-linearity with preloads and dead-zones nonlinearity was discussed [12]. Vörös extended the key variable separation identification method for a Hammerstein system with a two-segment piecewise-linear nonlinearity [13] to a Hammerstein system with a multi-segment piecewise-linear characteristic [14] and with a time-varying backlash [15]. This paper deal with dual-rate Hammerstein systems with a two-segment piecewise-linear nonlinearity in cascade with a linear dynamic system.…”
Section: Introductionmentioning
confidence: 99%
“…There are some contributions in the literature on the identification of systems with backlash, however it is assumed that the backlash is "straight" ie, straight lines approximate the upward and downward curves of the characteristic; see eg [3][4][5][6][7][8][9]. This simplifies the system description, however, in some cases it leads to inaccuracies.…”
Section: Introductionmentioning
confidence: 99%