Continuous-Time IO Systems Identification through Downsampled Models
European Control Conference
ISSN or ISBN
An indirect downsampling approach for continuous-time input/output system identification is proposed. This modus operandi was introduced to system identification through a subspace algorithm, where the input/output data set is partitioned into lower rate m subsets. Then, a state-space discrete-time model is identified by fusing the data subsets into a single one. In the present work the identification of the input/output downsampled model is performed by a least squares and a simplified refined instrumental variables (IV) procedures. In this approach, the inter-sample behaviour is preserved by the addition of fictitious inputs, leading to an increase of excitation requirements of the input signal. This over requirement is removed by directly estimating from the data the parameters of the transfer function numerator. The performance of the method is illustrated using the Rao-Garnier test system.
Ramos, Jose A.; Lopes dos Santos, Paulo; Azevedo Perdicoulis, Teresa Paula; Martins de Carvalho, Jorge L.; and Jank, Gerhard, "Continuous-Time IO Systems Identification through Downsampled Models" (2013). CEC Faculty Articles. 413.