Pin, G;
Chen, B;
Parisini, T;
(2017)
Robust finite-time estimation of biased sinusoidal signals: A volterra operators approach.
Automatica
, 77
pp. 120-132.
10.1016/j.automatica.2016.10.031.
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Abstract
A novel finite-time convergent estimation technique is proposed for identifying the amplitude, frequency and phase of a biased sinusoidal signal. Resorting to Volterra integral operators with suitably designed kernels, the measured signal is processed yielding a set of auxiliary signals in which the influence of the unknown initial conditions is removed. A second-order sliding mode-based adaptation law–fed by the aforementioned auxiliary signals–is designed for finite-time estimation of the frequency, amplitude, and phase. The worst case behavior of the proposed algorithm in presence of the bounded additive disturbances is fully characterized by Input-to-State Stability arguments. The effectiveness of the estimation technique is evaluated and compared with other existing tools via extensive numerical simulations.
| Type: | Article |
|---|---|
| Title: | Robust finite-time estimation of biased sinusoidal signals: A volterra operators approach |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1016/j.automatica.2016.10.031 |
| Publisher version: | http://dx.doi.org/10.1016/j.automatica.2016.10.031 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Finite-time estimation, Sinusoidal parameters estimation, Volterra operator, Kernels |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10107494 |
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