Data-driven modelling of LTI systems using symbolic regression

D. Khandelwal, R. Toth, P.M.J. Van den Hof

Research output: Contribution to conferenceAbstractAcademic

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The aim of this project is to automate the task of data-driven
identification of dynamical systems. The underlying goal is
to develop an identification tool that models a physical system
without distinguishing between classes of systems such
as linear, nonlinear or possibly even hybrid systems. Such
an identification tool would be able to mine data generated by the system to infer such structural knowledge, without relying on the expertise of a skilled user. This will allow researchers to shift their focus back from the modelling task to the actual utilization of the model. Such a research objective requires the identification technique to employ tools that are not targeted towards nuanced modelling tasks, but remain applicable for a very broad range of systems. Hence, we seek to develop a new framework for system identification that uses generic tools.
Original languageEnglish
Publication statusPublished - 2017
Event36th Benelux Meeting on Systems and Control, 28-30 March 2017, Spa, Belgium - Sol-Cress, Spa, Belgium
Duration: 28 Mar 201730 Mar 2017


Conference36th Benelux Meeting on Systems and Control, 28-30 March 2017, Spa, Belgium
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