An auxiliary model based least squares algorithm for a dual-rate state space system with time-delay using the data filtering

For dual-rate state space systems with time-delay, this paper combines the auxiliary model identification idea with the filtering technique, transforms the state space model into the identification model with different input and output sampling rates, and presents a filtering and auxiliary model based recursive least squares identification algorithm with finite measurement input-output data. Compared with the auxiliary model based recursive least squares algorithm, the proposed algorithm can generate more accurate parameter estimates and has a higher computational efficiency because the dimensions of its covariance matrices become small.