Title :
Bias-compensating method for a continuous-time model estimation by using adaptive observer
Author_Institution :
Fac. of Eng., Univ. of Tokushima, Tokushima, Japan
Abstract :
In this paper, a bias-compensating method for a continuous-time model estimation by using adaptive observer is proposed. It is assumed that the observation noise is a white Gaussian signal while there are no process noises. The proposed method is applicable for the identification in the closed loop environment when the plant has a pole on the imaginary axis. It is shown that the proposed estimate is consistent.
Keywords :
Gaussian noise; closed loop systems; compensation; continuous time systems; observers; white noise; adaptive observer; bias compensating method; closed loop environment; continuous time model estimation; imaginary axis; observation noise; white Gaussian signal; Adaptation models; Noise; Numerical models; Observers; Upper bound; Vectors; Adaptive filters; Bias compensation; Closed loop systems; Continuous-time systems; Parameter estimation;
Conference_Titel :
Control Conference (ECC), 2007 European
Conference_Location :
Kos
Print_ISBN :
978-3-9524173-8-6
