ℋ2 sub-optimal model reduction for second-order network systems

Autor:	Emma Gort, Xiaodong Cheng, Jacquelien M.A. Scherpen, Lanlin Yu
Přispěvatelé:	Control Systems, Dynamic Networks: Data-Driven Modeling and Control
Jazyk:	angličtina
Rok vydání:	2020
Předmět:	Reduction (complexity) Moment (mathematics) Matching (statistics) Dimension (vector space) Computer science Stability theory Order (ring theory) Topology
Zdroj:	CDC 2019 IEEE 58th Conference on Decision and Control, CDC 2019, 5062-5067 STARTPAGE=5062;ENDPAGE=5067;TITLE=2019 IEEE 58th Conference on Decision and Control, CDC 2019
ISSN:	0743-1546
Popis:	This paper studies a moment matching model reduction method for second-order network systems. For a given complex second-order network system, our goal is to find a reduced second-order network system that achieves moment matching. Firstly, the original second-order network system is split into an asymptotically stable subsystem and an average subsystem. Then, moment matching approach is implemented to reduce the dimension of the asymptotically stable subsystem. The resulting reduced-order model is combined with the average subsystem, leading to a reduced second-order system preserves the semistability. Subsequently, a specific coordinate transform allows for the reduced-order model to be converted to a complete network. A mass-spring-damper network demonstrates the effectiveness of the proposed method.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::078c6ef7542e21f4e64ba9787af53ac8 http://www.scopus.com/inward/record.url?scp=85082502730&partnerID=8YFLogxK Zobrazit plný text záznamu