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Robust Filtering Based on Probabilistic Descriptions of
Model Errors
Mikael Sternad
and
Anders Ahlén
2nd IFAC Workshop on System Structure and Control,
Prague, Czechoslovakia, September 3-5, 1992,
pp 156-159.
In Postscript :
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In Pdf 286K.
- Abstract:
-
A new approach to robust estimation of signals and
prediction of time-series is considered.
Signal and system parameter deviations are represented
as random variables, with known covariances.
A robust design is obtained
by minimizing the squared estimation error, averaged both
with respect to model errors and noise.
A polynomial solution, based on
averaged spectral factorizations and averaged
Diophantine equations, is derived. The robust
estimator is called a cautious Wiener filter. It
turns out to be no more
complicated to design than an ordinary Wiener filter.
- Related publications:
-
Paper in Automatica 1993,
with robust Wiener design and a feedforward design example.
Paper in IEEE Trans. AC 1995,
on robust MIMO Wiener filters and feedforward controllers.
PhD Thesis
by Kenth Öhrn May 1996.
Conference paper
on the corresponding dual design of robust feedforward controllers.
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