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The objective of this application is to provide a unifying framework for nonlinear system identification.
Today’s state-of-the art methods for system and control design are model based. The ever increasing demand for higher performance and efficiency pushes the systems in a nonlinear operation mode so that nonlinear models are required for their design and control. The model quality and the model building cost are becoming limiting factors for further technological developments.
Nonlinear system identification offers a systematic approach to obtain mathematical models for nonlinear dynamic systems, starting from experimental data. A wide variety of methods has been proposed in the past.
Project
A unifying approach to data driven modeling of nonlinear systems (FWOAL859)
The objective of this application is to provide a unifying framework for nonlinear system identification.
Today’s state-of-the art methods for system and control design are model based. The ever increasing demand for higher performance and efficiency pushes the systems in a nonlinear operation mode so that nonlinear models are required for their design and control. The model quality and the model building cost are becoming limiting factors for further technological developments.
Nonlinear system identification offers a systematic approach to obtain mathematical models for nonlinear dynamic systems, starting from experimental data. A wide variety of methods has been proposed in the past.
Date:1 Jan 2018 → 31 Dec 2021
Keywords:data, Non-linear systems, modeling
Disciplines:Electronics not elsewhere classified