Title :
Bounded error identification of time-varying parameters by RLS techniques
Author :
Bittanti, Sergio ; Campi, Marco
Author_Institution :
Dipartimento di Elettronica, Politecnico di Milano, Italy
fDate :
5/1/1994 12:00:00 AM
Abstract :
The performance of the recursive least squares algorithm with constant forgetting factor in the identification of time-varying parameters is studied in a stochastic framework. It is shown that the mean square tracking error keeps bounded if and only if the so-called covariance matrix of the algorithm is L1-bounded. Then, a feasibility range for the forgetting factor is worked out in correspondence of which the covariance matrix (and therefore the tracking error) keeps bounded
Keywords :
identification; least squares approximations; matrix algebra; parameter estimation; tracking; L1-bounded; RLS techniques; bounded error identification; constant forgetting factor; covariance matrix; feasibility range; mean square tracking error; recursive least squares algorithm; stochastic framework; time-varying parameters; tracking error; Covariance matrix; Equations; Filtering algorithms; Least squares methods; Mathematical model; Resonance light scattering; Signal processing algorithms; Stochastic processes; Time measurement; Time varying systems;
Journal_Title :
Automatic Control, IEEE Transactions on
