This chapter presents the identification of a web-winding system as a linear parameter varying (LPV) system with the reel radius as the time-varying parameter. This system is nonlinear, time-varying and input–output unstable. Two identification methods are considered: in the first one, an LPV model is estimated in a single step using a novel approach based on sparse identification and set membership optimality evaluation. In the second one, several local linear time-invariant (LTI) models are identified using classical identification algorithms, and the overall LPV model is constructed as a weighted sum of the local models. The two methods are applied to experimental data measured on a real web-winding machine.

Experimental modeling of a web-winding machine: LPV approaches / Vuelvas, Jose; Ruiz, Fredy; Novara, Carlo - In: Data-Driven Modeling, Filtering and Control: Methods and Applications[s.l] : IET the Institution of Engineering and Technology, 2019. - ISBN 9781785617133. - pp. 57-74 [10.1049/PBCE123E_ch4]

Experimental modeling of a web-winding machine: LPV approaches

Carlo Novara
2019

Abstract

This chapter presents the identification of a web-winding system as a linear parameter varying (LPV) system with the reel radius as the time-varying parameter. This system is nonlinear, time-varying and input–output unstable. Two identification methods are considered: in the first one, an LPV model is estimated in a single step using a novel approach based on sparse identification and set membership optimality evaluation. In the second one, several local linear time-invariant (LTI) models are identified using classical identification algorithms, and the overall LPV model is constructed as a weighted sum of the local models. The two methods are applied to experimental data measured on a real web-winding machine.
2019
9781785617133
Data-Driven Modeling, Filtering and Control: Methods and Applications
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2831718