Weighted Moments Based Identification of Continuous-Time Systems

نویسندگان

  • DORIN SENDRESCU
  • EMIL PETRE
  • DAN POPESCU
  • EUGEN BOBASU
چکیده

In this paper we present an algorithm for continuous-time model identification from sample data using the weighted power moments of the output signal of a linear, time-invariant system. While most of the latest methods used in identification utilize a discrete-time model, the moments method is an alternative approach to directly identify a continuous-time model from discrete-time data. The method defines a set of relationships between the power series coefficients of a stable transfer function and the power moments of the output signal of this system. Based on these relations, an algorithm for off-line parameter identification is developed. The method is applied to identify the parameters of a real experimental platform. Key-Words: off-line identification, weighted power moments, sampled data

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تاریخ انتشار 2007