Abstract
This paper focuses on the iterative identification problems for a class of Hammerstein nonlinear systems. By decomposing the system into two fictitious subsystems, a decomposition-based least squares iterative algorithm is presented for estimating the parameter vector in each subsystem. Moreover, a data filtering-based decomposition least squares iterative algorithm is proposed. The simulation results indicate that the data filtering-based least squares iterative algorithm can generate more accurate parameter estimates than the least squares iterative algorithm.
Original language | English |
---|---|
Pages (from-to) | 1895-1908 |
Number of pages | 14 |
Journal | Nonlinear Dynamics |
Volume | 83 |
Issue number | 4 |
Early online date | 29 Oct 2015 |
DOIs | |
Publication status | Published - 1 Mar 2016 |
Keywords
- data filtering
- iterative algorithm
- least squares
- model decomposition
- nonlinear system