Sensor diagnosis and state estimation for a class of skew symmetric time-varying systems

In this contribution we investigate the problem of simultaneous observer based sensor fault reconstruction and state estimation of a class of linear time-varying (LTV) systems that are skew-symmetric models. The main features concern the use of a bank of observers to detect and isolate faulty sensors and in the same time provide unbiased state estimation. On the other hand, we introduced a switching gain technique to deal with singular points. Stability analysis is achieved thanks to the Barbalat's lemma and without solving the well-known time-varying Sylvester equation. The proposed approach is extended to more general LTV systems of any order.

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