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Recursive identification under scarce measurements — convergence analysis
Authors:R. Sanchis  P. Albertos
Abstract:In this paper, the problem of recursive identification under scarce-data operation is addressed. The control action is assumed to be updated at a fixed rate, while the output is assumed to be measured synchronously with the input update, but with an irregular availability pattern. Under these conditions the use of pseudo-linear recursive algorithms is studied. The main result is the convergence analysis for the case of regular but scarce data availability. The existence of wrong attractors is demonstrated, and a local stability condition of the identification algorithm is derived.
Keywords:Missing-data   Unconventional sampling   Pseudo-linear recursive identification   Convergence analysis
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