Title :
Relative-error H∞ identification from autocorrelation data-a stochastic realization method
Author :
Wang, Weizheng ; Safonov, Michael G.
Author_Institution :
The Mathworks Inc., Natick, MA, USA
fDate :
7/1/1992 12:00:00 AM
Abstract :
A variant of the balanced stochastic truncation (BST) method for approximated realization of power spectrum matrices is shown to form the basis for an identification procedure that is well-suited to the task of determining relative-error-bounded approximate plant models for use in control design from input-output cross correlation data. Central to the theory is a novel L∞-norm bound on the relative-error between an exact realization of the data and BST approximate realization
Keywords :
identification; matrix algebra; time series; L∞-norm bound; approximated realization; balanced stochastic truncation; input-output cross correlation data; power spectrum matrices; relative-error H∞ identification; relative-error-bounded approximate plant models; time series; Autocorrelation; Differential equations; Fading; H infinity control; Kalman filters; Recursive estimation; Robust control; Robustness; Stochastic processes; Uncertainty;
Journal_Title :
Automatic Control, IEEE Transactions on
