Identification of Continuous-Time Systems with Unknown Time Delay by Nonlinear Least-Squares and Instrumental Variable Methods

Abstract

This paper considers the identification problem of continuous-time systems with unknown time delay from sampled input-output data. By using a digital prefilter, an approximated discrete-time estimation model is first derived, in which the system parameters remain in their original form and the time delay need not be an integral multiple of the sampling period. Then an iterative separable nonlinear least-squares (SEPNLS) method which estimates the time delay and transfer function parameters separably is derived. Furthermore, through investigation of the properties of the SEPNLS estimate, a novel separable nonlinear instrumental variable (SEPNIV) method is also proposed. Simulational results show that the SEPNIV method yields consistent estimates.