Distributed Group Coordination of Random Communication Constrained Cyber-Physical Systems Using Cloud Edge Computing

This paper studied the distributed group coordinated control problem of cyber-physical systems (CPSs) with multi-agent architecture. We build the distributed networked multi-group agent systems (NMGASs) with nonlinear and unknown dynamics via cloud edge computing. The common and challenging situations of random communication constraints in CPSs are considered, including network-induced delay, packet dropout, and packet disorder, which are treated as round-trip time (RTT) delay. To actively compensate for RTT delay and achieve coordination among all agents, a data-driven cloud edge predicted control strategy is designed. This strategy only needs to obtain the I/O measurement data of the systems, and can automatically carry out adaptive learning, which has more extensive application scenarios compared to model-based control methods. Theoretical analysis yields the conditions of simultaneous stability and consensus of the closed-loop systems with the proposed strategy. Finally, the practical examples are provided to illustrate the effectiveness of the proposed strategy.