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Kernel-Based Simultaneous Parameter-State Estimation for Continuous-Time Systems

Li, P; Boem, F; Pin, G; Parisini, T; (2019) Kernel-Based Simultaneous Parameter-State Estimation for Continuous-Time Systems. IEEE Transactions on Automatic Control 10.1109/TAC.2019.2953146. (In press). Green open access

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Abstract

In this note, the problem of jointly estimating the state and the parameters of continuous-time systems is addressed. Making use of suitably designed Volterra integral operators, the proposed estimator does not need the availability of time-derivatives of the measurable signals and the dependence on the unknown initial conditions is removed. As a result, the estimates converge to the true values in arbitrarily short time in a noise-free scenario. In the presence of bounded measurement and process disturbances, the estimation error is shown to be bounded. The numerical implementation aspects are dealt with and extensive simulation results are provides showing the effectiveness of the estimator.

Type: Article
Title: Kernel-Based Simultaneous Parameter-State Estimation for Continuous-Time Systems
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/TAC.2019.2953146
Publisher version: https://doi.org/10.1109/TAC.2019.2953146
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 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/10086880
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