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Robust H-2 Filtering for Structured Uncertainty:
The Performance of Probabilistic and Minimax Schemes.
Mikael Sternad,
Kenth Öhrn
and
Anders Ahlén
1995 European Control Conference,
Rome, Italy, September 1995, pp 87-92.
Also: Internal Report UPTEC 94090R, Dept. of Technology,
Uppsala University.
- Outline:
-
The performance of Kalman filters may be degraded in the presence
of model errors. A method for robust design, based on the
minimization of averaged mean square error criteria,
is proposed here. Its properties are compared to those of
an alternative minimax approach.
- Abstract:
-
A probabilistic approach to the robustification of
Kalman filters is presented.
It results in a higher order model, in which the uncertainty
can be taken into account by simply
modifying the noise covariance matrices.
The proposed method provides a systematic way of
performing this transformation.
The performance
of the robustified Kalman filter is
compared to that of a recently proposed
minimax H-2 scheme, based on two coupled Riccati
equations and a one-dimensional numerical search.
It is concluded that such methods should be used with
care, since their guaranteed performance may be
worse than that obtained by doing no filtering at all.
- Related publications:
-
PhD Thesis
by Kenth Öhrn May 1996, with details, examples
and generalizations.
Paper in IEEE Trans. AC 1995,
on the corresponding design of multivariable Wiener filters.
Paper in Automatica 1993,
which includes an alternative way of robustifying state
estimators.
- Source:
-
Pdf, 285K.
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