Auxiliary Model Based Maximum Likelihood Least Squares Iterative Estimation Algorithm for Bilinear Systems with Colored Noises

This paper mainly considers the parameter estimation of bilinear output-error systems with colored noises. According to the auxiliary model identification idea, the unmeasurable inner variables (true outputs) in the system model are replaced with the output of an auxiliary model, and an auxiliary model based maximum likelihood least squares iterative algorithm is studied to estimate the parameters of bilinear output-error systems. The simulation results show that the proposed algorithm is effective for identifying the bilinear output-error systems.