Title :
Parameter subset identification by recursive least squares
Author :
Pizarro, O. ; Sbarbaro, D.
Author_Institution :
Dept. of Electr. Eng., Univ. de Concepcion, Chile
Abstract :
A technique for recursive least squares (RLS) identification of only a subset of parameters of a linear model is presented. Based on the decomposition of the least squares (LS) problem, an exact solution and a recursive approximation are developed. Identification of a subset of parameters is useful in adaptive control techniques based on cost function identification
Keywords :
adaptive control; least squares approximations; recursive estimation; RLS identification; adaptive control; cost function identification; parameter subset identification; recursive approximation; recursive least squares identification; Adaptive control; Cost function; Dynamic programming; Equations; Least squares approximation; Least squares methods; Matrix decomposition; Minimization methods; Parameter estimation; Vectors;
Conference_Titel :
American Control Conference, 1998. Proceedings of the 1998
Conference_Location :
Philadelphia, PA
Print_ISBN :
0-7803-4530-4
DOI :
10.1109/ACC.1998.703281
