带输入约束的一阶采样多智能体系统包含控制

Containment Control for First-order Sampling Multi-agent System with Input Constraints

研究了切换通信拓扑下的带输入约束的一阶采样多智能体系统包含控制问题,其目的是只利用采样数据实现一组输入受限的智能体进入到由领导者构成的凸区域中。首先提出了一种基于投影的包含控制算法。其次将所有智能体与凸包的最大距离构造成李亚普诺夫函数,采用模型变化、凸分析等方法证明了在通信拓扑的并集中,只要每个智能体能直接或间接至少收到一个领导者的信息,所有智能体最终就能收敛到凸区域内。最后,数值仿真结果证明了理论结果的正确性。

The containment control problem of a first-order sampling multi-agent system with input constraints switching communication topology. Its purpose is to use only sampled data to realize a group of agents with input-constrained into the convex area formed by the leader. First, a projection-based containment control algorithm is proposed. Secondly, the largest distance between agents and the convex hull is define as a Lyapunov function, and the method of model transformation and convex analysis is used to prove that in the union of communication topology, as long as each agent can directly or indirectly receive at least one leader’s Information, all agents can finally converge to the convex area. Finally, the numerical simulation results prove the correctness of the theoretical results.