Experimental modeling of a web-winding machine: LPV approaches

Jose Vuelvas; Fredy Ruiz; Carlo Novara

doi:10.1049/pbce123e_ch4

Experimental modeling of a web-winding machine: LPV approaches

Jose Vuelvas
, Fredy Ruiz
, Carlo Novara

Department of Electronic Engineering

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

Abstract

This chapter presents the identification of aweb-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.

Original language	English
Title of host publication	Data-Driven Modeling, Filtering and Control
Publisher	Institution of Engineering and Technology
Pages	57-73
Number of pages	17
ISBN (Electronic)	9781785617126
DOIs	https://doi.org/10.1049/pbce123e_ch4
State	Published - 01 Jan 2019

Keywords

Combinatorial mathematics
Combinatorial mathematics
Control applications to materials handling
Control technology and theory
Identification
Identification algorithms
Input-output instability
Input-output stability
LPV
Linear parameter varying systems
Linear parameter-varying system
Local linear time-invariant models
Local models
Nonlinear control systems
Nonlinear control systems
Nonlinear system
Other manufacturing processes
Production equipment
Reel radius
Set membership optimality evaluation
Set theory
Simulation, modelling and identification
Sparse identification
Stability in control theory
Time-varying control systems
Time-varying parameter
Time-varying systems
Web-winding machine
Weighted sum
Winding (process)

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10.1049/pbce123e_ch4

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title = "Experimental modeling of a web-winding machine: LPV approaches",

abstract = "This chapter presents the identification of aweb-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.",

keywords = "Combinatorial mathematics, Combinatorial mathematics, Control applications to materials handling, Control technology and theory, Identification, Identification algorithms, Input-output instability, Input-output stability, LPV, Linear parameter varying systems, Linear parameter-varying system, Local linear time-invariant models, Local models, Nonlinear control systems, Nonlinear control systems, Nonlinear system, Other manufacturing processes, Production equipment, Reel radius, Set membership optimality evaluation, Set theory, Simulation, modelling and identification, Sparse identification, Stability in control theory, Time-varying control systems, Time-varying parameter, Time-varying systems, Web-winding machine, Weighted sum, Winding (process)",

author = "Jose Vuelvas and Fredy Ruiz and Carlo Novara",

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AU - Vuelvas, Jose

AU - Ruiz, Fredy

AU - Novara, Carlo

N1 - Publisher Copyright: © The Institution of Engineering and Technology 2019.

PY - 2019/1/1

Y1 - 2019/1/1

N2 - This chapter presents the identification of aweb-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.

AB - This chapter presents the identification of aweb-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.

KW - Combinatorial mathematics

KW - Control applications to materials handling

KW - Control technology and theory

KW - Identification

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KW - Reel radius

KW - Set membership optimality evaluation

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KW - Simulation, modelling and identification

KW - Sparse identification

KW - Stability in control theory

KW - Time-varying control systems

KW - Time-varying parameter

KW - Time-varying systems

KW - Web-winding machine

KW - Weighted sum

KW - Winding (process)

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DO - 10.1049/pbce123e_ch4

M3 - Chapter

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SP - 57

EP - 73

BT - Data-Driven Modeling, Filtering and Control

PB - Institution of Engineering and Technology

ER -

Experimental modeling of a web-winding machine: LPV approaches

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Keywords

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