A novel differentiator:A compromise between super twisting and linear algorithms - Archive ouverte HAL
Communication Dans Un Congrès Année : 2017

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

Résumé

Based on the frequency argument, a novel secondorder sliding mode differentiator with a variable exponent is proposed in this article. The super twisting differentiator(exponent = 0, 5) is not sensible to perturbation but its accuracy isdegraded when the signal is affected by the noise. The linearobserver (exponent= 1) has better property in the presence of noisebut is less robust to perturbations. The goal of this paper isto propose a trade-off between the exact differentiator andlinear observer. To reach this objective, the exponent parameter ismade variable. In the absence of noise exponent goes to 0; 5 andtends to 1 when the noise increases. In free-noise case andwith or without perturbation, the novel differentiator behavesas a super twisting differentiator (exact differentiation). Whenthe signal is affected by noise, only a practical stability of thedifferentiator is ensured. Finally simulation results are givento show that the novel differentiator has better performancescompared to differentiators having exponent fixed.
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Dates et versions

hal-01588632 , version 1 (15-09-2017)

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Malek Ghanes, Jean-Pierre Barbot, Leonid Fridman, Arie Levant. A novel differentiator:A compromise between super twisting and linear algorithms. IEEE CDC, Dec 2017, Melbourne, Australia. ⟨10.1109/cdc.2017.8264460⟩. ⟨hal-01588632⟩
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