Exponential Consensus Analysis for Multiagent Networks Based on Time-Delay Impulsive Systems
研究了有向拓扑下时滞多智能体网络的一致性问题，提出结合非时滞、时滞和瞬时信息的算法，并分析了存在外部扰动时的鲁棒H∞性能，给出了指数一致性的充分条件。
In this paper, some consensus problems are considered for time-delay multiagent networks with directed topologies. Since agents are driven by not only long-term but instant contact with their neighbors, dynamic behaviors of agents can be described by impulsive differential equations. A period of non time-delay and time-delay information and instantaneous information are adopted in the proposed algorithms. Moreover, robust problems with the corresponding ${H_{\infty }}$ performance are investigated for multiagent networks with external disturbances. Sufficient conditions are obtained such that consensus can be exponentially reached for multiagent networks with/without external disturbances. Numerical examples are given to demonstrate the effectiveness of the obtained theoretical results.