论文部分内容阅读
针对如何在多智能体网络中无中心式地求解动态一致平均的问题,提出了一种分布式动态一致平均(DDAC)算法。首先,针对动态一致平均问题建立数学模型。然后,设计DDAC算法对动态变化的信号进行一致平均跟踪。最后,通过数值仿真实验结果表明,相比现有的一阶动态一致平均(FODAC)算法和二阶动态一致平均(SODAC)算法,所提出的分布式动态一致平均(DDAC)算法具有更好的收敛性能。
Aiming at the problem of how to solve the dynamic uniform averaging without center in multi-agent networks, a distributed dynamic consistent averaging (DDAC) algorithm is proposed. First of all, a mathematical model is established for the dynamic uniform averaging problem. Then, the DDAC algorithm is designed to track the dynamically changing signals uniformly and uniformly. Finally, numerical simulation results show that the proposed distributed dynamic consistent averaging (DDAC) algorithm has better performance than the existing first-order dynamic coincidence average (FODAC) algorithm and second-order dynamic coincidence average (SODAC) Convergence performance.