4.4 Article

ON CONVERGENCE OF VOLTERRA SERIES EXPANSION OF A CLASS OF NONLINEAR SYSTEMS

期刊

ASIAN JOURNAL OF CONTROL
卷 19, 期 3, 页码 1089-1102

出版社

WILEY
DOI: 10.1002/asjc.1485

关键词

Volterra series; nonlinear systems; convergence bound

资金

  1. GRF project of HK RGC [15206514]
  2. NSFC [61374041]
  3. Hong Kong Polytechnic University

向作者/读者索取更多资源

A fundamental issue in conducting the analysis and design of a nonlinear system via Volterra series theory is how to ensure the excitation magnitude and/or model parameters will be in the appropriate range such that the nonlinear system has a convergent Volterra series expansion. To this aim, parametric convergence bounds of Volterra series expansion of nonlinear systems described by a NARX model, which can reveal under what excitation magnitude or within what parameter range a given NARX system is able to have a convergent Volterra series expansion subject to any given input signal, are investigated systematically in this paper. The existing bound results often are given as a function of the maximum input magnitude, which could be suitable for single-tone harmonic inputs but very conservative for complicated inputs (e.g. multi-tone or arbitrary inputs). In this study, the output response of nonlinear systems is expressed in a closed form, which is not only determined by the input magnitude but also related to the input energy or waveform. These new techniques result in more accurate bound criteria, which are not only functions of model parameters and the maximum input magnitude but also consider a factor reflecting the overall input energy or wave form. This is significant to practical applications, since the same nonlinear system could exhibit chaotic behavior subject to a simple single-tone input but might not with respect to other different input signals (e.g. multi-tone inputs) of the same input magnitude. The results provide useful guidance for the application of Volterra series-based theory and methods from an engineering point of view. The Duffing equation is used as a benchmark example to show the effectiveness of the results.

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