Bias compensation based parameter estimation for dual-rate sampled-data systems

This paper deals with the parameter identification for dual-rate sampled-data systems, aiming to identify the systems directly from the dual-rate sampled data. The main idea is carried out by two steps. Firstly, a polynomial transformation technique is employed to change the output-error model for single-rate systems to the one that can directly use the dual-rate sampled data. Secondly, a bias compensation based identification is demonstrated to get the unbiased parameter estimates of the transferred dual-rate model. Simulation examples are given to illustrate the proposed algorithm.