Title :
Identification for Hammerstein Systems Using Extended Least Squares Algorithm
Author_Institution :
Acad. of Math. & Syst. Sci., Beijing
Abstract :
The extended least squares (ELS) algorithm is applied to identifying the Hammerstein system, where the nonlinear static function f (.) is expressed as a linear combination of basic functions with unknown coefficients. Strong consistency of the estimates is established and their convergent rates are obtained as well.
Keywords :
identification; least squares approximations; nonlinear functions; Hammerstein systems; extended least squares algorithm; identification; nonlinear static function; Algorithm design and analysis; Control systems; Cost function; Instruments; Iterative algorithms; Least squares methods; Linear systems; Mathematics; Parameter estimation; ARMAX; Hammerstein system; extended least squares; strong consistency;
Conference_Titel :
Control Conference, 2007. CCC 2007. Chinese
Conference_Location :
Hunan
Print_ISBN :
978-7-81124-055-9
Electronic_ISBN :
978-7-900719-22-5
DOI :
10.1109/CHICC.2006.4347212
