Abstract
We present a multi-observer approach for the parameter and state estimation of continuous-time nonlinear systems. For nominal parameter values in the known parameter set, state observers are designed with a robustness property. At any time instant, one observer is selected by a given criterion to provide its state estimate and its corresponding nominal parameter value. Provided that a persistency of excitation condition holds, we guarantee the convergence of state and parameter estimates up to a given margin of error which can be reduced by increasing the number of observers. The potential computational burden of the scheme is eased by introducing a dynamic parameter re-sampling technique, where the nominal parameter values are iteratively updated using a zoom-in procedure on the parameter set. We illustrate the efficacy of the algorithm on a model of neural dynamics.
Original language | English |
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Title of host publication | 53rd IEEE Conference on Decision and Control |
Subtitle of host publication | December 15-17, 2014. Los Angeles, California, USA |
Editors | Andrew R. Teel |
Place of Publication | Piscataway NJ USA |
Publisher | IEEE, Institute of Electrical and Electronics Engineers |
Pages | 1067-1072 |
Number of pages | 6 |
ISBN (Electronic) | 9781467360906, 9781479977451 |
ISBN (Print) | 9781479977468 |
DOIs | |
Publication status | Published - 2014 |
Externally published | Yes |
Event | IEEE Conference on Decision and Control 2014 - J.W. Marriott Hotel, Los Angeles, United States of America Duration: 15 Dec 2014 → 17 Dec 2014 Conference number: 53rd http://cdc2014.ieeecss.org/cfp.php https://ieeexplore.ieee.org/xpl/conhome/7027307/proceeding (Proceedings) |
Conference
Conference | IEEE Conference on Decision and Control 2014 |
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Abbreviated title | CDC 2014 |
Country/Territory | United States of America |
City | Los Angeles |
Period | 15/12/14 → 17/12/14 |
Internet address |