Scalable analysis methods for sparse large-scale systems.
Anders Rantzer, Lund University
Abstract:
In analysis of large-scale dynamic systems, it is of fundamental interest to understand how specifications on local components and interconnections influence global properties of the system. In this presentation, we consider linear time-invariant systems described by sparse matrices. Properties of interest are stability and quadratic performance specifications such as passivity and input-output gain. In particular, for systems with sparsity structure corresponding to a chordal graph, we show that scalable performance conditions can be expressed without conservatism.