Paper Info
Title
A New Controllability Gramian For Semistable Systems And Its Application To Approximation Of Directed Networks
Abstract
In this paper, we propose a new definition of a controllability Gramian for semistable systems, which is then used for model reduction of network systems. The system under consideration is modeled as single integrators that inter-connected with each other according to a connected directed network. In the proposed method, the complexity of the network is reduced through a graph clustering method which aggregates the vertices if they respond similarly with respect to external inputs. Here, the similarity of the vertices is computed based on the new Gramian. The reduced-order model is obtained by a Petrov-Galerkin projection where the projection matrices are constructed from the resulting clustering. The reduced system preserves the network structure, and the approximation error between the full-order and reduced-order models is shown to be always bounded. Finally, the proposed approach is illustrated by an example.
Year
Venue
Field
2017
2017 IEEE 56TH ANNUAL CONFERENCE ON DECISION AND CONTROL (CDC)
Topology,Mathematical optimization,Controllability,Vertex (geometry),Computer science,Gramian matrix,Cluster analysis,Clustering coefficient,Approximation error,Bounded function,Controllability Gramian
DocType
ISSN
Citations 
Conference
0743-1546
0
PageRank 
References 
Authors
0.34
0
2
Name
Order
Citations
PageRank
Xiaodong Cheng131.48
Jacquelien M. A. Scherpen249195.93