Two-stage least squares based iterative identification algorithm for controlled autoregressive moving average (CARMA) systems

Abstract

A two-stage least squares based iterative (two-stage LSI) identification algorithm is derived for controlled autoregressive moving average (CARMA) systems. The basic idea is to decompose a CARMA system into two subsystems and to identify each subsystem, respectively. Because the dimensions of the involved covariance matrices in each subsystem become small, the proposed algorithm has a high computational efficiency. The simulation results indicate that the proposed algorithm is effective.