Abstract
AbstractIn this paper, we address the data-driven design of observers for the process monitoring and control purposes. Instead of identifying a standard state space model, our design schemes are based on the identification of the so-called parity subspace. Two design schemes are developed, which allow a direct design of (a) observer-based fault detection systems (b) a full order observer for the estimation of the process state variables. The achieved results are illustrated by a benchmark example.
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