Robust Connectivity for Resilient Consensus via Optimal Control in Multi-Agent System subject to Dynamic Topology

In this paper, we propose a methodology that ensures robust connectivity for resilient consensus in multi-agent systems subject to dynamic topology. It also ensures the use of optimal control inputs for tracking desired trajectories even in the presence of non-cooperative agents. The methodology has three components: a) the reconfiguration protocol ensures robust connectivity, b) the sliding window mean subsequence reduced (SW-MSR) approach ensures resilient consensus, and c) the nonlinear model predictive control (NMPC) generates optimal control inputs to achieve the desired topology while tracking respective desired trajectories. The associated analytical results demonstrate the asymptotic consensus and stability of the system. The simulation experiments validate the effectiveness of the proposed methodology that can be used for real-world applications.