Modeling and identification of uncertain-input systems

Abstract

In this work, we present a new class of models, called uncertain-input models, that allows us to treat system-identification problems in which a linear system is subject to a partially unknown input signal. To encode prior information about the input or the linear system, we use Gaussian-process models. We estimate the model from data using the empirical… (More)

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Cite this paper

@article{Risuleo2017ModelingAI, title={Modeling and identification of uncertain-input systems}, author={Riccardo Sven Risuleo and Giulio Bottegal and H{\aa}kan Hjalmarsson}, journal={CoRR}, year={2017}, volume={abs/1709.03421} }