Recursive identification under scarce measurements - Convergence analysis

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. © 2002 Published by Elsevier Science Ltd.

Año de publicación:

2002

Keywords:

• missing-data
• Pseudo-Linear Recursive Identification
• Convergence Analysis
• Unconventional sampling

Fuente:

scopus