Average Consensus for Switching Topology Networks with Privacy Protection

This work contributed to solve the average consensus problem of switching topology networks with privacy protection. Starting from the well-known average consensus algorithm and considering the impact of uncertain environment on communication topology, we propose a simple but effective privacy protection mechanism, which can reach an accurate average consensus even if the communication link between agents changes. By dividing the initial state of the agent, a linear combination of explicit state and implicit state is obtained. The explicit state of agents interacts with each other, while the implicit state is only stored in itself. This algorithm does not need the assistance of any third party and has low computational complexity. Theoretical analysis and numerical simulation show that the true state of agents is not only protected, but also can reach an accurate average consensus.