Chen, B;
Pin, G;
Ng, WM;
Hui, SYR;
Parisini, T;
(2018)
An adaptive-observer-based robust estimator of multi-sinusoidal signals.
IEEE Transactions on Automatic Control
, 63
(6)
pp. 1528-1541.
10.1109/TAC.2017.2752007.
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Abstract
This paper presents an adaptive-observer-based robust estimation methodology of the amplitudes, frequencies, and phases of biased multi-sinusoidal signals in the presence of bounded perturbations on the measurement. The parameters of the sinusoidal components are estimated online, and the update laws are individually controlled by an excitation-based switching logic enabling the update of a parameter only when the measured signal is sufficiently informative. This way doing, the algorithm is able to tackle the problem of overparameterization (i.e., when the internal model accounts for a number of sinusoids that is larger than the true spectral content) or temporarily fading sinusoidal components. The stability analysis proves the existence of a tuning parameter set, for which the estimator's dynamics are input-to-state stable with respect to bounded measurement disturbances. The performance of the proposed estimation approach is evaluated and compared with the other existing tools by extensive simulation trials and real-time experiments.
Type: | Article |
---|---|
Title: | An adaptive-observer-based robust estimator of multi-sinusoidal signals |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1109/TAC.2017.2752007 |
Publisher version: | http://dx.doi.org/10.1109/TAC.2017.2752007 |
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. |
UCL classification: | UCL UCL > Provost and Vice Provost Offices 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-pp.ucl.ac.uk/id/eprint/10107501 |
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