Fully Distributed Consensus Tracking of Stochastic Nonlinear Multiagent Systems With Markovian Switching Topologies via Intermittent Control
研究了随机非线性多智能体系统在马尔可夫切换拓扑下的完全分布式一致性跟踪问题，提出仅依赖邻居相对状态的间歇自适应控制协议，降低能耗且无需全局信息。
The fully distributed consensus tracking of stochastic nonlinear multiagent systems (MASs) is investigated with Markovian switching topologies and intermittent control strategy, where the dynamics of agents are depicted by Itô differential equations and the leader’s information is just known for a fraction of followers. The switching mechanism of interaction topologies is modeled as a Markov process. A novel class of fully distributed control protocols is proposed via intermittent control method, which is only associated with the relative state measurements of neighbors and does not involve any global information. Meanwhile, the control gains are designed to be intermittently adaptive, which can effectively reduce energy consumption and avoid the gains being larger than those needed in practice. Several sufficient conditions and corresponding proofs are provided by using the Lyapunov stability theory. Finally, numerical simulation is presented to state the feasibility of the theoretical results.