CUED Publications database

Feedback for nonlinear system identification

Burghi, T and Schoukens, M and Sepulchre, R (2019) Feedback for nonlinear system identification. In: European Control Conference (ECC), 2019-6-25 to 2019-6-28, Naples, Italy, pp. 1344-1349..

Full text not available from this repository.


Motivated by neuronal models from neuroscience, we consider the system identification of simple feedback structures whose behaviors include nonlinear phenomena such as excitability, limit-cycles and chaos. We show that output feedback is sufficient to solve the identification problem in a two-step procedure. First, the nonlinear static characteristic of the system is extracted, and second, using a feedback linearizing law, a mildly nonlinear system with an approximately-finite memory is identified. In an ideal setting, the second step boils down to the identification of a LTI system. To illustrate the method in a realistic setting, we present numerical simulations of the identification of two classical systems that fit the assumed model structure.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Divisions: Div F > Control
Depositing User: Cron Job
Date Deposited: 08 Oct 2019 01:09
Last Modified: 09 Sep 2021 01:12
DOI: doi:10.23919/ECC.2019.8795769