Design and modeling aspects in multivariable iterative learning control

L.L.G. Blanken; S.H. Koekebakker; T.A.E. Oomen

doi:10.1109/CDC.2016.7799114

Design and modeling aspects in multivariable iterative learning control

L.L.G. Blanken, S.H. Koekebakker, T.A.E. Oomen

Control Systems Technology

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

4 Citations (Scopus)

1 Downloads (Pure)

Abstract

Iterative Learning Control (ILC) can significantly improve the performance of systems that perform repeating tasks. Typically, several decentralized ILC controllers are designed and implemented. Such ILC designs tacitly ignore interaction. The aim of this paper is to further analyze the consequences of interaction in ILC, and develop a solution framework, covering a spectrum of systematic decentralized designs to centralized designs. The proposed set of solutions differs in design, i.e., performance and robustness, and modeling requirements, which are investigated in detail. The benefits and differences are demonstrated through a simulation study

Original language	English
Title of host publication	2016 IEEE 55th Conference on Decision and Control, CDC 2016
Place of Publication	Piscataway
Publisher	Institute of Electrical and Electronics Engineers
Pages	5502-5507
Number of pages	6
ISBN (Electronic)	978-1-5090-1837-6
DOIs	https://doi.org/10.1109/CDC.2016.7799114
Publication status	Published - 27 Dec 2016
Event	55th IEEE Conference on Decision and Control (CDC 2016) - Aria Resort and Casino, Las Vegas, United States Duration: 12 Dec 2016 → 14 Dec 2016 Conference number: 55 http://cdc2016.ieeecss.org/

Conference

Conference	55th IEEE Conference on Decision and Control (CDC 2016)
Abbreviated title	CDC02016
Country/Territory	United States
City	Las Vegas
Period	12/12/16 → 14/12/16
Internet address	http://cdc2016.ieeecss.org/

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10.1109/CDC.2016.7799114

Cite this

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title = "Design and modeling aspects in multivariable iterative learning control",

abstract = "Iterative Learning Control (ILC) can significantly improve the performance of systems that perform repeating tasks. Typically, several decentralized ILC controllers are designed and implemented. Such ILC designs tacitly ignore interaction. The aim of this paper is to further analyze the consequences of interaction in ILC, and develop a solution framework, covering a spectrum of systematic decentralized designs to centralized designs. The proposed set of solutions differs in design, i.e., performance and robustness, and modeling requirements, which are investigated in detail. The benefits and differences are demonstrated through a simulation study",

author = "L.L.G. Blanken and S.H. Koekebakker and T.A.E. Oomen",

year = "2016",

month = dec,

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doi = "10.1109/CDC.2016.7799114",

language = "English",

pages = "5502--5507",

booktitle = "2016 IEEE 55th Conference on Decision and Control, CDC 2016",

publisher = "Institute of Electrical and Electronics Engineers",

address = "United States",

note = "55th IEEE Conference on Decision and Control (CDC 2016), CDC02016 ; Conference date: 12-12-2016 Through 14-12-2016",

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}

Blanken, LLG , Koekebakker, SH & Oomen, TAE 2016, Design and modeling aspects in multivariable iterative learning control. in 2016 IEEE 55th Conference on Decision and Control, CDC 2016., 7799114, Institute of Electrical and Electronics Engineers, Piscataway, pp. 5502-5507, 55th IEEE Conference on Decision and Control (CDC 2016), Las Vegas, Nevada, United States, 12/12/16. https://doi.org/10.1109/CDC.2016.7799114

Design and modeling aspects in multivariable iterative learning control. / Blanken, L.L.G.; Koekebakker, S.H.; Oomen, T.A.E.
2016 IEEE 55th Conference on Decision and Control, CDC 2016. Piscataway: Institute of Electrical and Electronics Engineers, 2016. p. 5502-5507 7799114.

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

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AB - Iterative Learning Control (ILC) can significantly improve the performance of systems that perform repeating tasks. Typically, several decentralized ILC controllers are designed and implemented. Such ILC designs tacitly ignore interaction. The aim of this paper is to further analyze the consequences of interaction in ILC, and develop a solution framework, covering a spectrum of systematic decentralized designs to centralized designs. The proposed set of solutions differs in design, i.e., performance and robustness, and modeling requirements, which are investigated in detail. The benefits and differences are demonstrated through a simulation study

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BT - 2016 IEEE 55th Conference on Decision and Control, CDC 2016

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Design and modeling aspects in multivariable iterative learning control

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