Accelerating the convergence rate of consensus for second-order multi-agent systems by memory information☆ ☆

The consensus problem of second-order multi-agent systems (MASs) has been widely studied due to its applications in various areas. This paper utilizes the agents' memory information to accelerate the convergence rate of consensus for discrete-time second-order MASs. For the case of one-tap memory, explicit formulas for the optimal convergence rate and control parameters are derived by using a novel method based on the Jury stability criterion. It is proved that the optimal convergence rate with one-tap memory is faster than that without memory. For the case of M-tap memory, an iterative algorithm is given to derive the control parameters to accelerate the convergence rate. Numerical examples further illustrate the theoretical results. (c) 2024 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.