H2 model reduction for diffusively coupled second-order networks by convex-optimization. (March 2022)

• Record Type: Journal Article
• Authors: Yu, Lanlin; Cheng, Xiaodong; Scherpen, Jacquelien M.A.; Xiong, Junlin
• Is Part Of: Automatica. Volume 137(2022)
• Publication Date: 2022-03
• Subjects: Second-order networks -- Diffusive coupling -- H2 model reduction -- Linear matrix inequality -- Convex-optimization; Automatic control -- Periodicals; Automation -- Periodicals; 629.805
• DOI: 10.1016/j.automatica.2021.110118
• Languages: English
• ISSNs: 0005-1098

Abstract

Abstract: This paper provides an H 2 optimal scheme for reducing diffusively coupled second-order systems evolving over undirected networks. The aim is to find a reduced-order model that not only approximates the input–output mapping of the original system but also preserves crucial structures, such as the second-order form, asymptotically stability, and diffusive couplings. To this end, an H 2 optimal approach based on a convex relaxation is used to reduce the dimension, yielding a lower order asymptotically stable approximation of the original second-order network system. Then, a novel graph reconstruction approach is employed to convert the obtained model to a reduced system that is interpretable as an undirected diffusively coupled network. Finally, the effectiveness of the proposed method is illustrated via a large-scale networked mass–spring–damper system.