Title :
A two-stage least squares based iterative parameter estimation algorithm for feedback nonlinear systems based on the model decomposition
Author :
Peipei Hu ; Yongsong Xiao ; Rui Ding
Author_Institution :
Key Lab. of Adv. Process Control for Light Ind. (Minist. of Educ.), Jiangnan Univ., Wuxi, China
Abstract :
A two-stage least squares based iterative parameter estimation algorithm is proposed for identifying a feedback nonlinear system with the open-loop being a controlled autoregressive moving average model from input-output data. The identification model is bilinear on two unknown parameter vectors. By decomposing a system into two subsystems, we identify each subsystem, which is linear about a parameter vector. The simulation example is provided.
Keywords :
autoregressive moving average processes; bilinear systems; feedback; iterative methods; least squares approximations; open loop systems; parameter estimation; vectors; autoregressive moving average model; bilinear identification model; feedback nonlinear system identification; input-output data; model decomposition; open-loop; parameter vectors; two-stage least squares based iterative parameter estimation algorithm; Autoregressive processes; Computational modeling; Iterative methods; Least squares approximations; Mathematical model; Nonlinear systems; Vectors;
Conference_Titel :
American Control Conference (ACC), 2013
Conference_Location :
Washington, DC
Print_ISBN :
978-1-4799-0177-7
DOI :
10.1109/ACC.2013.6580689
