Real-time on-line identification of a nonlinear continuous-time plant using Hartley modulating functions method

Abstract

In this paper, a new real-time on-line batch scheme recursive LS approach is proposed for physically-based parameters identification of nonlinear continuous-time plant using Hartley modulating functions (HMF) and facilitated by interactive real-time toolbox. The method is implemented by moving a fixed window size of time series data one step forward at each sampling time and by updating recursively the regressand vector and regression matrix of the system HMF model that consists of updating the sequential Hartley transforms and spectra for each coming sample of input-output signals. The method is applied on a separately excited DC motor and load plant to examine the performance and potential of the proposed real-time on-line identification approach.