Accelerating the Convergence Rate of Consensus for Second-Order Multi-Agent Systems by Memory Information

Abstract

This paper utilizes the agent's memory in accelerated consensus for second-order multi-agent systems (MASs). In the case of one-tap memory, explicit formulas for the optimal consensus convergence rate and control parameters are derived by applying the Jury stability criterion. It is proved that the optimal consensus convergence rate with one-tap memory is faster than that without memory. In the case of M-tap memory, an iterative algorithm is given to derive the control parameters to accelerate the convergence rate. Moreover, the accelerated consensus with one-tap memory is extended to the formation control, and the control parameters to achieve the fastest formation are obtained. Numerical examples further illustrate the theoretical results.