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Identification of continuous-time state-space models from non-uniform fast-sampled data

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4 Author(s)
Yuz, J.I. ; Electron. Eng. Dept., Univ. Tec. Federico Santa Maria (UTFSM), Valparaíso, Chile ; Alfaro, J. ; Agüero, J.C. ; Goodwin, G.C.

In this study, we apply the expectation-maximisation (EM) algorithm to identify continuous-time state-space models from non-uniformly fast-sampled data. The sampling intervals are assumed to be small and uniformly bounded. The authors use a parameterisation of the sampled-data model in incremental form in order to modify the standard formulation of the EM algorithm for discrete-time models. The parameters of the incremental model converge to the parameter of the continuous-time system description as the sampling period goes to zero. The benefits of the proposed algorithm are successfully demonstrated via simulation studies.

Published in:

Control Theory & Applications, IET  (Volume:5 ,  Issue: 7 )