A novel differentiator: A compromise between super twisting and linear algorithms

M. Ghanes, J. P. Barbot, L. Fridman, A. Levant

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Based on the frequency argument, a novel second order sliding mode differentiator with a variable exponent α is proposed in this article. The super twisting differentiator (α = 0, 5) is not sensible to perturbation but its accuracy is degraded when the signal is affected by the noise. The linear observer (α = 1) has better property in the presence of noise but is less robust to perturbations. The goal of this paper is to propose a trade-off between the exact differentiator and linear observer. To reach this objective, the parameter α is made variable. In the absence of noise α goes to 0, 5 and tends to 1 when the noise increases. In free-noise case and with or without perturbation, the novel differentiator behaves as a super twisting differentiator (exact differentiation). When the signal is affected by noise, only a practical stability of the differentiator is ensured. Finally simulation results are given to show that the novel differentiator has better performances compared to differentiators having α fixed.

Original languageEnglish
Title of host publication2017 IEEE 56th Annual Conference on Decision and Control, CDC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages5415-5419
Number of pages5
ISBN (Electronic)9781509028733
DOIs
StatePublished - 18 Jan 2018
Event56th IEEE Annual Conference on Decision and Control, CDC 2017 - Melbourne, Australia
Duration: 12 Dec 201715 Dec 2017

Publication series

Name2017 IEEE 56th Annual Conference on Decision and Control, CDC 2017
Volume2018-January

Conference

Conference56th IEEE Annual Conference on Decision and Control, CDC 2017
Country/TerritoryAustralia
CityMelbourne
Period12/12/1715/12/17

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