Distributed Adaptive Containment Control of Stochastic Nonlinear Multiagent Systems
针对具有多个动态领导者和未知协方差的随机多智能体系统，提出一种分布式自适应包含跟踪控制方法，使跟随者输出指数收敛到领导者输出的凸包内。
A novel distributed adaptive containment tracking control method is proposed for stochastic multiagent systems (MASs). Unlike existing results, we consider a more general system with both multiple dynamic leaders and unknown covariance. The control input of each agent system depends only on the states of its neighbors and its local states. When dealing with unknown time-varying covariance, we do not need to know its bound but use a proper estimation. Then, by using the backstepping design method, an adaptive law and a distributed adaptive tracking controller are designed. Using stochastic analysis and graph theory, it is proved that the outputs of the followers converge exponentially to the convex hull spanned by the outputs of the dynamic leaders under the condition that all signals of the closed-loop system remain bounded in probability and the tracking error is tunable. Finally, we illustrate the feasibility of the design scheme through numerical simulation.