Necessary and Sufficient Conditions for Consensus of Double-Integrator Multi-Agent Systems With Measurement Noises

An average consensus protocol is proposed for continuous-time double-integrator multi-agent systems with measurement noises under fixed topologies. The time-varying control gain is employed to attenuate noises. The closed-loop system is therefore a time-varying linear stochastic differential equation. By determining the state transition matrix of this closed-loop system, the dynamic characteristics of the multi-agent system can be fully described. It is proved that in the noisy communication environment the average consensus can be achieved if and only if the communication topology is a balanced and strongly connected graph, and the time-varying control gain satisfies the stochastic approximation-type conditions. Under the proposed protocol, the position of each agent is convergent in mean square to a common random variable whose mathematical expectation is the average of initial positions and initial velocities of all agents in the system, while each agent´s velocity is convergent in mean square to a common random variable whose mathematical expectation and variance are both zero.