On Neighbor Information Utilization in Distributed Receding Horizon Control for Consensus-Seeking
研究一阶多智能体系统中分布式滚动时域控制如何利用邻居信息达成一致，给出了有限时域和无限时域下保证一致性的条件，并指出最优利用方式可最快收敛。
This paper investigates the issue on how to utilize neighbor information in the distributed receding horizon control (RHC)-based consensus problem for first-order multiagent systems. The distributed RHC-based consensus problem is first formulated in a general framework in terms of using neighbor information. Based on the framework, a sufficient condition on utilizing neighbor information to ensure consensus is developed for the finite horizon case. For the infinite horizon case, a necessary and sufficient condition is proposed, and the best way of using neighbor information to achieve fastest convergence rate is also presented. It is shown that: 1) the way of utilizing neighbor information plays an important role in reaching consensus; 2) the parameter that ensures consensus is related with the network topology; and 3) the best convergence rate in consensus can be attained if the neighbor information is appropriately utilized. Simulation studies verify the proposed theoretical results.