Title :
Unbiased identification of systems with nonparametric uncertainty
Author :
Feng, Chun-Bo ; Zhang, Ying
Author_Institution :
Res. Inst. of Autom., Southeast Univ., Nanjing, China
fDate :
5/1/1995 12:00:00 AM
Abstract :
The set-membership identification of systems with parametric and nonparametric uncertainty is studied. The bias induced by the additive noise is eliminated by using the bias-eliminated least squares method proposed previously by us (1991). A prefilter is connected to the input terminal of the system, so that some zeros are inserted to the system. By using the information obtained from these known zeros, the bias induced by the additive noise is eliminated
Keywords :
identification; least squares approximations; linear systems; noise; poles and zeros; uncertain systems; additive noise; least squares method; linear systems; nonparametric uncertainty; prefilter; set-membership; unbiased systems identification; zeros; Additive noise; Automation; Digital filters; Least squares methods; Noise measurement; Noise robustness; Statistics; Transfer functions; Uncertainty; Zinc;
Journal_Title :
Automatic Control, IEEE Transactions on
