Abstract
According to the iterative identification technique and the hierarchical identification principle, this paper presents a two-stage gradient based and a least squares based iterative parameter estimation algorithms (i.e., the hierarchical gradient based iterative algorithm and the hierarchical least squares based iterative algorithm) for controlled autoregressive autoregressive moving average systems. The proposed two-stage least squares based iterative algorithm requires less computation compared with the least squares based iterative algorithm. The simulation results indicate that the two-stage least squares based iterative algorithm converges faster than the two-stage gradient based iterative algorithm.
Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
