Iterative identification methods for input nonlinear multivariable systems using the key-term separation principle

作者：Shen, Qianyan; Ding, Feng^*

来源：Journal of the Franklin Institute, 2015, 352(7): 2847-2865.

DOI：10.1016/j.jfranklin.2015.05.005

• PARAMETER-ESTIMATION
• STOCHASTIC-SYSTEMS
• TRACKING CONTROL
• ALGORITHMS
• STATE

Identification for input nonlinear multivariable systems lies in that there exist the products of the parameters of the nonlinear block and the linear block. By means of the key-term separation principle, a subsystem least squares based iterative algorithm and a subsystem gradient based iterative algorithm are proposed for input nonlinear systems described by controlled autoregressive moving average models. Finally, the proposed methods are tested using numerical examples.

• 出版日期2015-7
• 单位江南大学