Title :
Techniques to improve the regressor matrix condition for real-time parameter identification
Author :
Ngo, Anhtuan D. ; Doman, David B.
Author_Institution :
VACA, Air Force Res. Lab., Wright-Patterson AFB, OH, USA
Abstract :
In this paper, on-line parameter identification algorithms that consider the collinearity of the system measurements are presented. Using null-space injection and regularized linear regression with stochastic constraints, the proposed methods improve the estimates of the system parameters
Keywords :
linear systems; parameter estimation; stochastic processes; collinearity; null-space injection; real-time parameter identification; regressor matrix condition; regularized linear regression; stochastic constraints; system measurements; system parameters; Acceleration; Control systems; Equations; Laboratories; Parameter estimation; Real time systems; Stability; System identification; Vehicles; Yield estimation;
Conference_Titel :
American Control Conference, 2001. Proceedings of the 2001
Conference_Location :
Arlington, VA
Print_ISBN :
0-7803-6495-3
DOI :
10.1109/ACC.2001.946208
