Distributed Optimization Based on a Multiagent System in the Presence of Communication Delays
研究了存在时变通信延迟的连续时间多智能体系统的分布式优化问题，揭示了最优解与系统平衡点的关系，推导了收敛的充分条件，并给出了采样数据通信方案和参数估计应用。
In this paper, distributed optimization is addressed based on a continuous-time multiagent system in the presence of time-varying communication delays. First, the relationship between optimal solutions and the equilibrium points of the multiagent system with time delay is revealed. Next, delay-dependent and delay-independent sufficient conditions in form of linear matrix inequality are derived for ascertaining convergence to optimal solutions, in the cases of slow-varying delay and fast-varying delay. Furthermore, a set of conditions are also obtained for the delay-free case. In addition, a sampled-data communication scheme is presented based on the conditions for the fast varying delay systems. Simulation results are presented to substantiate the theoretical results. An application for distributed parameter estimation is also given.