Four-Stage Recursive Least Squares Algorithm for CARARMA Systems

This paper derives four -stage recursive least squares algorithm for Controlled Autoregressive Autoregressive Moving Average (CARARMA) systems. By applying the decomposition technique, (CARARMA) system decompose into four subsystems that include one parameter vector each. The proposed algorithm improves the accuracy of estimated parameters and decrease the computational burden compared with recursive generalized least squares algorithm. The simulation example is given to indicate the efficiency of the algorithm.