Energy Equipartition Stabilization and Cascading Resilience Optimization for Geospatially Distributed Cyber-Physical Network Systems

This paper develops three novel hybrid stabilization techniques addressing fast energy equipartition for cyber-physical network systems, establishes an optimization-based network topology design framework to achieve cascading resilience and efficiency of geospatially distributed physical networks, and discusses the future application of the proposed approach to power network systems. Thus, the main contributions of this paper are three-fold. First, we present three hybrid distributed stabilization architectures for cyber-physical network systems to achieve the robust performance of geospatial physical networks by mimicking the dynamic behavior of thermodynamic systems. The proposed stabilization architectures are constructed in such a way that each stabilizer has a one-directional energy transfer from a plant to itself, and exchanges energy with its neighboring stabilizers. Second, to balance resilience to cascading failures and efficiency of energy flow in geospatially distributed physical networks, we propose an entropy metric-based multiobjective optimization framework for network topology design to characterize this resilience-efficiency trade-off design in networks. Moreover, we propose a novel cascade-connectivity swarm optimization algorithm which combines swarm intelligence and graph theory together to solve this multiobjective optimization problem. Finally, we apply our hybrid stabilization techniques and topology design algorithms to power network systems, and simulation studies are carried out to show the efficacy of the proposed approach.