Data-driven LPV synthesis: the FIR controller case

Tom Bloemers; Roland Tóth; Tom Oomen

Data-driven LPV synthesis: the FIR controller case

Tom Bloemers
, Roland Tóth
, Tom Oomen

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic

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Abstract

Current state-of-the-art control design techniques in the Linear Parameter-Varying (LPV) framework are dependent on the availability of a parametric model of the to be controlled system. Such models are often obtained through firstprinciple modeling. In practical situations, this often results in complex models for which LPV control design can be difficult. Alternatively, system identification methods can be used. On the other hand, control synthesis techniques based on Frequency-Response-Function (FRF) measurements for linear time-invariant systems are available, avoiding the intermediate procedure of first-principle modeling (see, e.g., [1, 2, 3]). The aim of this work is to present a data-driven LPV control synthesis method for Finite Impulse Response (FIR) filters

Original language	English
Title of host publication	38th Benelux Meeting on Systems and Control
Editors	Panos Patrinos, Ivan Markovsky, Wim Michiels, Jan Swevers, Steffen Waldherr
Pages	111
Number of pages	1
Publication status	Published - 2019
Event	38th Benelux Meeting on Systems and Control 2019 - Center Parcs De Vossemeren, Lommel, Belgium Duration: 19 Mar 2019 → 21 Mar 2019

Conference

Conference	38th Benelux Meeting on Systems and Control 2019
Country/Territory	Belgium
City	Lommel
Period	19/03/19 → 21/03/19

Cite this

@inproceedings{dd3831b371b449afb4f8b8efa10c9a29,

title = "Data-driven LPV synthesis: the FIR controller case",

abstract = "Current state-of-the-art control design techniques in the Linear Parameter-Varying (LPV) framework are dependent on the availability of a parametric model of the to be controlled system. Such models are often obtained through firstprinciple modeling. In practical situations, this often results in complex models for which LPV control design can be difficult. Alternatively, system identification methods can be used. On the other hand, control synthesis techniques based on Frequency-Response-Function (FRF) measurements for linear time-invariant systems are available, avoiding the intermediate procedure of first-principle modeling (see, e.g., [1, 2, 3]). The aim of this work is to present a data-driven LPV control synthesis method for Finite Impulse Response (FIR) filters",

author = "Tom Bloemers and Roland T{\'o}th and Tom Oomen",

year = "2019",

language = "English",

pages = "111",

editor = "Panos Patrinos and Ivan Markovsky and Wim Michiels and Jan Swevers and Steffen Waldherr",

booktitle = "38th Benelux Meeting on Systems and Control",

note = "38th Benelux Meeting on Systems and Control 2019 ; Conference date: 19-03-2019 Through 21-03-2019",

}

TY - GEN

T1 - Data-driven LPV synthesis: the FIR controller case

AU - Bloemers, Tom

AU - Tóth, Roland

AU - Oomen, Tom

PY - 2019

Y1 - 2019

N2 - Current state-of-the-art control design techniques in the Linear Parameter-Varying (LPV) framework are dependent on the availability of a parametric model of the to be controlled system. Such models are often obtained through firstprinciple modeling. In practical situations, this often results in complex models for which LPV control design can be difficult. Alternatively, system identification methods can be used. On the other hand, control synthesis techniques based on Frequency-Response-Function (FRF) measurements for linear time-invariant systems are available, avoiding the intermediate procedure of first-principle modeling (see, e.g., [1, 2, 3]). The aim of this work is to present a data-driven LPV control synthesis method for Finite Impulse Response (FIR) filters

AB - Current state-of-the-art control design techniques in the Linear Parameter-Varying (LPV) framework are dependent on the availability of a parametric model of the to be controlled system. Such models are often obtained through firstprinciple modeling. In practical situations, this often results in complex models for which LPV control design can be difficult. Alternatively, system identification methods can be used. On the other hand, control synthesis techniques based on Frequency-Response-Function (FRF) measurements for linear time-invariant systems are available, avoiding the intermediate procedure of first-principle modeling (see, e.g., [1, 2, 3]). The aim of this work is to present a data-driven LPV control synthesis method for Finite Impulse Response (FIR) filters

M3 - Conference contribution

SP - 111

BT - 38th Benelux Meeting on Systems and Control

A2 - Patrinos, Panos

A2 - Markovsky, Ivan

A2 - Michiels, Wim

A2 - Swevers, Jan

A2 - Waldherr, Steffen

T2 - 38th Benelux Meeting on Systems and Control 2019

Y2 - 19 March 2019 through 21 March 2019

ER -

Data-driven LPV synthesis: the FIR controller case

Abstract

Conference

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