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arXiv · 2103.10820

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

Rodrigo A. González·Cristian R. Rojas·Håkan Hjalmarsson
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Abstract

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.

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Rodrigo A. González, Cristian R. Rojas, Håkan Hjalmarsson. 2021-03-19. Non-causal regularized least-squares for continuous-time system identification with band-limited input excitations. https://arxiv.org/abs/2103.10820

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