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Robust l1 estimation using the Popov-Tsypkin multiplier with application to robust fault detection

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2 Author(s)
Collins, E.G., Jr. ; Dept. of Mech. Eng., Florida State Univ., Tallahassee, FL, USA ; Song, T.

Considers the design of robust l1 estimators based on multiplier theory (which is intimately related to mixed structured singular value theory) and the application of robust l1 estimators to robust fault detection. The key to estimator-based, robust fault detection is to generate residuals which are robust against plant uncertainties and external disturbance inputs, which in turn requires the design of robust estimators. Specifically, the Popov-Tsypkin multiplier is used to develop an upper bound on an l1 cost function over an uncertainty set. The robust l1 estimation problem is formulated as a parameter optimization problem in which the upper bound is minimized subject to a Riccati equation constraint. The estimation algorithm has two stages. The first stage solves a mixed-norm H2/l1 estimation problem. In the second stage the l1 estimator is made robust. The robust l1 estimation framework is then applied to robust fault detection of dynamic systems

Published in:

American Control Conference, 1999. Proceedings of the 1999  (Volume:6 )

Date of Conference:

1999

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