Consensus in Plug-and-Play Heterogeneous Dynamical Networks: A Passivity Compensation Approach
This addresses consensus in modular networks for applications like distributed control, but it is incremental as it builds on existing passivity-based methods.
The paper tackles output consensus in heterogeneous dynamical networks with nonlinear couplings and noise by proposing a passivity-compensation approach that uses surplus passivity in coupling links to offset node passivity shortages, enabling plug-and-play modularity without global reanalysis.
This paper investigates output consensus in heterogeneous dynamical networks within a plug-and-play framework. The networks are interconnected through nonlinear diffusive couplings and operate in the presence of measurement and communication noise. Focusing on systems that are input feedforward passive (IFP), we propose a passivity-compensation approach that exploits the surplus passivity of coupling links to locally offset shortages of passivity at the nodes. This mechanism enables subnetworks to be interconnected without requiring global reanalysis, thereby preserving modularity. Specifically, we derive locally verifiable interface conditions, expressed in terms of passivity indices and coupling gains, to guarantee that consensus properties of individual subnetworks are preserved when forming larger networks.