Abstract | ||
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We present a new design methodology of sampled-data observers that unifies and generalizes many existing design methodologies. The approach is based on continuous-time observers that feature two characteristics: (i) exhibit exponential convergence in the noiseless case with respect to a given Observer Lyapunov Function, and (ii) satisfy an Input-to-Output Stability property with respect to output measurement noise. The design approach applies to a wide class of systems and yields sampled-data observers that inherit these two performance characteristics of the underlying continuous-time observer. The main component of the proposed sampled-data observer is a novel output predictor that encompasses both inter-sample predictors and Zero-Order-Hold predictors. (C) 2020 Elsevier B.V. All rights reserved. |
Year | DOI | Venue |
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2020 | 10.1016/j.sysconle.2020.104760 | SYSTEMS & CONTROL LETTERS |
Keywords | DocType | Volume |
Nonlinear observers,Sampled-data observers,Inter-sample predictor | Journal | 144 |
ISSN | Citations | PageRank |
0167-6911 | 1 | 0.37 |
References | Authors | |
0 | 3 |
Name | Order | Citations | PageRank |
---|---|---|---|
Iasson Karafyllis | 1 | 592 | 55.06 |
Tarek Ahmed-Ali | 2 | 245 | 26.90 |
F. Giri | 3 | 110 | 29.41 |