Abstract
This letter proposes a differentiator for sampled signals with bounded noise and bounded second derivative. It is based on a linear program derived from the available sample information and requires no further tuning beyond the noise and derivative bounds. A tight bound on the worst-case accuracy, i.e., the worst-case differentiation error, is derived, which is the best among all causal differentiators and is moreover shown to be obtained after a fixed number of sampling steps. Comparisons with the accuracy of existing high-gain and sliding-mode differentiators illustrate the obtained results.
Originalsprache | englisch |
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Aufsatznummer | 9448332 |
Seiten (von - bis) | 938-943 |
Seitenumfang | 6 |
Fachzeitschrift | IEEE Control Systems Letters |
Jahrgang | 6 |
DOIs | |
Publikationsstatus | Veröffentlicht - 2022 |
ASJC Scopus subject areas
- Steuerung und Optimierung
- Steuerungs- und Systemtechnik