The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.
Uniform Robust Exact Differentiator
Abstract
The differentiators based on the Super-Twisting Algorithm (STA) yield finite-time and theoretically exact convergence to the derivative of the input signal, whenever this derivative is Lipschitz. However, the convergence time grows unboundedly when the initial conditions of the differentiation error grow. In this technical note a Uniform Robust Exact Differentiator (URED) is introduced. The URED is based on a STA modification and includes high-degree terms providing finite-time, and exact convergence to the derivative of the input signal, with a convergence time that is bounded by some constant independent of the initial conditions of the differentiation error. Strong Lyapunov functions are used to prove the convergence of the URED.
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Sánchez-Torres, J. D., Gómez-Gutiérrez, D., López, E., & Loukianov, A. G. (2018) · IMA Journal of Mathematical Control and Information · doi:10.1093/imamci/dnx004 · Cited by 570
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Polyakov, A., & Fridman, L. (2014) · Journal of the Franklin Institute · doi:10.1016/j.jfranklin.2014.01.002 · Cited by 420
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Metadata
- Authors
- Cruz-Zavala, E., Moreno, J. A., & Fridman, L. M.
- Venue
- IEEE Transactions on Automatic Control
- Published
- 2011-11
- Volume
- 56
- Issue
- 11
- Pages
- 2727-2733
- ISSN
- 0018-9286 (ISSN-L)
- 1558-2523
- OpenAlex
- W2097223915
- Cited by
- 559
- References
- 14
- FWCI
- 26.55
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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