Robust finite-time parameter estimation using a hybrid systems framework

M. Hartman; N.W. Bauer; A.R. Teel

doi:10.1109/TAC.2012.2194334

Robust finite-time parameter estimation using a hybrid systems framework

M. Hartman, N.W. Bauer, A.R. Teel

Control Systems Technology

Research output: Contribution to journal › Article › Academic › peer-review

12 Citations (Scopus)

Abstract

This note investigates the problem of parameter estimation for a class of nonlinear systems. We show that by placing a member of this class of systems into a hybrid dynamical system, we can identify its parameter exactly and in finite time. Furthermore, by using tools developed for hybrid systems, we show that the estimation has robust properties. In particular, the hybrid system contains a compact globally asymptotically stable set where the stability is robust to small perturbations. We also present conditions that ensure convergence of the parameter estimate.

Original language	English
Pages (from-to)	2956-2962
Number of pages	7
Journal	IEEE Transactions on Automatic Control
Volume	57
Issue number	11
DOIs	https://doi.org/10.1109/TAC.2012.2194334
Publication status	Published - 2012

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abstract = "This note investigates the problem of parameter estimation for a class of nonlinear systems. We show that by placing a member of this class of systems into a hybrid dynamical system, we can identify its parameter exactly and in finite time. Furthermore, by using tools developed for hybrid systems, we show that the estimation has robust properties. In particular, the hybrid system contains a compact globally asymptotically stable set where the stability is robust to small perturbations. We also present conditions that ensure convergence of the parameter estimate.",

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AB - This note investigates the problem of parameter estimation for a class of nonlinear systems. We show that by placing a member of this class of systems into a hybrid dynamical system, we can identify its parameter exactly and in finite time. Furthermore, by using tools developed for hybrid systems, we show that the estimation has robust properties. In particular, the hybrid system contains a compact globally asymptotically stable set where the stability is robust to small perturbations. We also present conditions that ensure convergence of the parameter estimate.

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