Abstract
The paper proposes a systematic framework for efficient decomposition of Linear Parameter Varying (LPV) systems. Our aim is to reveal the topological structure of the system, to facilitate various analysis and synthesis methods. For this purpose, first we extend the notion of Gramian based interaction measure for parameter dependent systems. However, the metric is based on the solution of an iterative optimization, subject to Linear Matrix Inequality (LMI) constraints. Therefore, in order to ease the computation burden, we apply a modal decomposition to the system. A simple structured Gramian computation is introduced, with fast conic programming. The proposed methodology is illustrated by a numerical example.
| Original language | English (US) |
|---|---|
| Title of host publication | 2018 IEEE Conference on Decision and Control, CDC 2018 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 5898-5903 |
| Number of pages | 6 |
| ISBN (Electronic) | 9781538613955 |
| DOIs | |
| State | Published - Jan 18 2019 |
| Event | 57th IEEE Conference on Decision and Control, CDC 2018 - Miami, United States Duration: Dec 17 2018 → Dec 19 2018 |
Publication series
| Name | Proceedings of the IEEE Conference on Decision and Control |
|---|---|
| Volume | 2018-December |
| ISSN (Print) | 0743-1546 |
Conference
| Conference | 57th IEEE Conference on Decision and Control, CDC 2018 |
|---|---|
| Country | United States |
| City | Miami |
| Period | 12/17/18 → 12/19/18 |
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Cite this
A Model Decomposition Framework for LPV Systems. / Luspay, Tamas; Peni, Tamas; Seiler Jr, Peter J; Vanek, Balint.
2018 IEEE Conference on Decision and Control, CDC 2018. Institute of Electrical and Electronics Engineers Inc., 2019. p. 5898-5903 8618676 (Proceedings of the IEEE Conference on Decision and Control; Vol. 2018-December).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - A Model Decomposition Framework for LPV Systems
AU - Luspay, Tamas
AU - Peni, Tamas
AU - Seiler Jr, Peter J
AU - Vanek, Balint
PY - 2019/1/18
Y1 - 2019/1/18
N2 - The paper proposes a systematic framework for efficient decomposition of Linear Parameter Varying (LPV) systems. Our aim is to reveal the topological structure of the system, to facilitate various analysis and synthesis methods. For this purpose, first we extend the notion of Gramian based interaction measure for parameter dependent systems. However, the metric is based on the solution of an iterative optimization, subject to Linear Matrix Inequality (LMI) constraints. Therefore, in order to ease the computation burden, we apply a modal decomposition to the system. A simple structured Gramian computation is introduced, with fast conic programming. The proposed methodology is illustrated by a numerical example.
AB - The paper proposes a systematic framework for efficient decomposition of Linear Parameter Varying (LPV) systems. Our aim is to reveal the topological structure of the system, to facilitate various analysis and synthesis methods. For this purpose, first we extend the notion of Gramian based interaction measure for parameter dependent systems. However, the metric is based on the solution of an iterative optimization, subject to Linear Matrix Inequality (LMI) constraints. Therefore, in order to ease the computation burden, we apply a modal decomposition to the system. A simple structured Gramian computation is introduced, with fast conic programming. The proposed methodology is illustrated by a numerical example.
UR - http://www.scopus.com/inward/record.url?scp=85062181742&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85062181742&partnerID=8YFLogxK
U2 - 10.1109/CDC.2018.8618676
DO - 10.1109/CDC.2018.8618676
M3 - Conference contribution
T3 - Proceedings of the IEEE Conference on Decision and Control
SP - 5898
EP - 5903
BT - 2018 IEEE Conference on Decision and Control, CDC 2018
PB - Institute of Electrical and Electronics Engineers Inc.
ER -