Two-stage Recursive Least Squares Parameter Estimation Algorithm for Multivariate Output-error Autoregressive Moving Average Systems

2019 ◽  
Vol 17 (6) ◽  
pp. 1547-1557 ◽  
Author(s):  
Yunze Guo ◽  
Lijuan Wan ◽  
Ling Xu ◽  
Feng Ding ◽  
Ahmed Alsaedi ◽  
...  
Keyword(s):  
Parameter Estimation ◽  
Least Squares ◽  
Moving Average ◽  
Estimation Algorithm ◽  
Recursive Least Squares ◽  
Autoregressive Moving Average ◽  
Two Stage ◽  
Output Error ◽  
Parameter Estimation Algorithm

scholarly journals Least-Squares Parameter Estimation Algorithm for a Class of Input Nonlinear Systems

2012 ◽  
Vol 2012 ◽  
pp. 1-14 ◽  
Author(s):  
Weili Xiong ◽  
Wei Fan ◽  
Rui Ding
Keyword(s):  
Parameter Estimation ◽  
Nonlinear Systems ◽  
Least Squares ◽  
Moving Average ◽  
Estimation Algorithm ◽  
Autoregressive Moving Average ◽  
Parameter Estimates ◽  
Persistent Excitation ◽  
Estimation Algorithms ◽  
Parameter Estimation Algorithm

This paper studies least-squares parameter estimation algorithms for input nonlinear systems, including the input nonlinear controlled autoregressive (IN-CAR) model and the input nonlinear controlled autoregressive autoregressive moving average (IN-CARARMA) model. The basic idea is to obtain linear-in-parameters models by overparameterizing such nonlinear systems and to use the least-squares algorithm to estimate the unknown parameter vectors. It is proved that the parameter estimates consistently converge to their true values under the persistent excitation condition. A simulation example is provided.

Sign in / Sign up

Export Citation Format

Share Document