IDENTIFICATION OF TIME DELAYS IN LINEAR STOCHASTIC-SYSTEMS

This paper presents a new approach to the explicit identification of a n input time delay in continuous-time linear systems. The system model is converted to a discrete-time version, assuming that a digital comp uter is to be used for time delay estimation and control. A recursive identification algorithm based on parallel Kalman filtering and Bayes' estimation is developed. The sampling rate is adapted during the time delay estimation process using the most recent estimate of the time d elay. This method assures that the estimate of the time delay approach es the true value with each successive iteration. The proposed method also has the advantage of a fast convergence rate because prior knowle dge of the delay, if available, can be effectively utilized.