On efficient parametric identification methods for linear discrete stochastic systems

Authors:
Yu. V. Tsyganova;M. V. Kulikova
Affiliations:
Ul'yanovsk State University, Ul'yanovsk, Russia;Lisbon Technical University, Lisbon, Portugal
Venue:
Automation and Remote Control
Year:
2012

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Abstract

We construct a numerically stable algorithm (with respect to machine rounding errors) of adaptive Kalman filtering in order to solve the parametric identification problem for linear stationary stochastic discrete systems. We solve the problem in the state space. The proposed algorithm is formulated in terms of an orthogonal square-root covariance filter which lets us avoid a standard implementation of the Kalman filter.