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.
Original language | English |
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Article number | 9448332 |
Pages (from-to) | 938-943 |
Number of pages | 6 |
Journal | IEEE Control Systems Letters |
Volume | 6 |
DOIs | |
Publication status | Published - 2022 |
Keywords
- Differentiation
- estimation
- observers
- optimization
ASJC Scopus subject areas
- Control and Optimization
- Control and Systems Engineering