Identification for dual-rate systems with colored noises using FIR-RELS methods

This paper studies modeling and identification problems for dual-rate systems with colored noises. The state-space models are derived for the systems with different input and output updating periods, furthermore the corresponding transfer functions are obtained. To solve the difficulty of identification models with unmeasurable noises terms, the FIR-RELS method is presented in this paper. The basic idea is to approximate the noise model by FIR (Finite Impulse Response) model, then using the RELS (Recursive Extended Least Squares) method to estimate the process model parameters. Finally, the simulation results show that the proposed method has good performance than RLS (Recursive Least Squares) and other algorithms.