Non-causal regularized least-squares for continuous-time system identification with band-limited input excitations

Part of proceedings: ISBN 978-1-6654-3659-5, QC 20230117
In continuous-time system identification, the intersample behavior of the input signal is known to play a crucial role in the performance of estimation methods. One common input behavior assumption is that the spectrum of the input is band-limited. The sinc interpolation property of these input signals yields equivalent discrete-time representations that are non-causal. This observation, often overlooked in the literature, is exploited in this work to study non-parametric frequency response estimators of linear continuous-time systems. We study the properties of non-causal least-square estimators for continuous-time system identification, and propose a kernel-based non-causal regularized least-squares approach for estimating the band-limited equivalent impulse response. The proposed methods are tested via extensive numerical simulations.

In:Proceedings 2021 60th IEEE conference on decision and control (CDC): Institute of Electrical and Electronics Engineers (IEEE), s. 114-119

By the author/editor: González, Rodrig ...; Rojas, Cristian ...; Hjalmarsson, Håk ...

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ENGINEERING AND TECHNOLOGY: ENGINEERING AND ...; and Electrical Engin ...; and Control Engineer ...

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