A major problem for today’s large-scale networked systems is to certify the required stability, performance, and safety properties using analytical and computational models. The existing methods for such certification are severely limited in their ability to cope with the number of physical components and the complexity of their interactions We address this problem with a compositional approach that derives network-level guarantees from key structural properties of the subsystems and their interactions, rather than tackle the system model as a whole. The foundational tool in our approach is the established dissipativity theory, enriched with modern computational techniques. Dissipativity properties serve as abstractions of the detailed dynamical models of the subsystems and allow us to decompose intractably large certification problems into subproblems of manageable size. We leverage large-scale optimization techniques to detect useful dissipativity properties and exploit interconnection symmetries for further computational savings. Case studies demonstrate the applicability of the methods to biological networks, vehicle platoons, and Internet congestion control.
