Identification of Continuous Time-Delay Systems Using the Genetic Algorithm
Tomohiro HACHINO, Zi-Jiang YANG, Teruo TSUJI
This paper proposes a novel method of identification of continuous time-delay systems from sampled input-output 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 multiples of the sampling period. Then an identification method combining the genetic algorithm (GA) with the common linear least squares (LS) method or the instrumental variable (IV) method 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 systems where the time-delays in the individual input channels may differ each other. Simulation results show that our method yields consistent estimates even in the presence of high measurement noises.