Identification of Parameters and Time Delays of Continuous Systems using the Genetic Algorithm

Abstract

This report proposes a novel method of identification of continuous time-delay systems from sampled inputoutput data. By the aid of a digital pre-filter, 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 identification method combining the common linear least squares (LS) method or the instrumental variable (IV) method with the genetic algorithm (GA) is proposed. That is, the time-delay is selected by the GA, and the system parameters are estimated by the LS or IV method. Furthermore, the proposed method is extended to the case of multi-input multi-output(MIMO) systems where the time-delays in the individual input channels may differ each other. Simulation results show that our method yields accurate estimates even in the presence of high measurement noises.