The leaderless, prescribed performance consensus problem for groups of agents with antagonistic interactions is addressed for the first time in this paper. We consider agents modeled by pure feedback nonlinear systems with unknown dynamics and an agent communication network described by a signed digraph with a directed spanning tree. A new proportional and integral (PI) variable transformation is proposed that enables the solution of the problem of leaderless bipartite consensus with prescribed performance by recasting it into a regulation problem with prescribed performance, which in turn we solve by a low complexity distributed control law. The algorithm guarantees uniform boundedness of all closed-loop signals and prescribed performance for the bipartite consensus error. Simulations verify the validity of our theoretical analysis.

本文首次解决了具有拮抗作用的代理商群体的无领导者规定的绩效共识问题。我们考虑由具有未知动力学的纯反馈非线性系统和由有向有向生成树的有向有向图描述的代理通信网络建模的代理。提出了一种新的比例积分（PI）变量变换，该变换可以通过将其重塑为具有规定性能的调节问题来解决具有规定性能的无领导者两方共识问题，而这又可以由低复杂度的分布式控制律来解决。该算法保证了所有闭环信号的均匀有界性和针对二分共识误差的规定性能。仿真验证了我们理论分析的有效性。