Journal
MATHEMATICAL AND COMPUTER MODELLING
Volume 53, Issue 9-10, Pages 1664-1669Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.mcm.2010.12.034
Keywords
System modelling; Recursive identification; Iterative identification; Parameter estimation; Least squares; Multivariable systems
Categories
Funding
- National Natural Science Foundation of China
Ask authors/readers for more resources
Difficulties of identification for multivariable controlled autoregressive moving average (ARMA) systems lie in that there exist unknown noise terms in the information vector, and the iterative identification can be used for the system with unknown terms in the information vector. By means of the hierarchical identification principle, those noise terms in the information vector are replaced with the estimated residuals and a least squares based iterative algorithm is proposed for multivariable controlled ARMA systems. The simulation results indicate that the proposed algorithm is effective. (C) 2011 Published by Elsevier Ltd
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available