Imperial College London
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ProfessorThomasParisini

Faculty of Engineering, Department of Electrical and Electronic Engineering

Chair in Industrial Control, Head of Group for CAP
 
 
 
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Contact

 

+44 (0)20 7594 6240t.parisini Website

 
 
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Location

 

1114Electrical EngineeringSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Chen:2018:10.1109/TAC.2017.2752007,
author = {Chen, B and Pin, G and Ng, WM and Hui, SYR and Parisini, T},
doi = {10.1109/TAC.2017.2752007},
journal = {IEEE TRANSACTIONS ON AUTOMATIC CONTROL},
pages = {1618--1631},
title = {An Adaptive-Observer-Based Robust Estimator of Multi-sinusoidal Signals},
url = {http://dx.doi.org/10.1109/TAC.2017.2752007},
volume = {63},
year = {2018}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - This paper presents an adaptive observer-based robust estimation methodology of the amplitudes, frequencies and phases of biased multi-sinusoidal signals in presence of bounded perturbations on the measurement. The parameters of the sinusoidal components are estimated on-line 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 over-parametrization (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 other existing tools by extensive simulation trials and real-time experiments.
AU  - Chen,B
AU  - Pin,G
AU  - Ng,WM
AU  - Hui,SYR
AU  - Parisini,T
DO  - 10.1109/TAC.2017.2752007
EP  - 1631
PY  - 2018///
SN  - 0018-9286
SP  - 1618
TI  - An Adaptive-Observer-Based Robust Estimator of Multi-sinusoidal Signals
T2  - IEEE TRANSACTIONS ON AUTOMATIC CONTROL
UR  - http://dx.doi.org/10.1109/TAC.2017.2752007
UR  - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000433367600006&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR  - http://hdl.handle.net/10044/1/51015
VL  - 63
ER  -
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