Distributed Neuro-Adaptive Formation Control for Uncertain Multi-Agent Systems: Node- and Edge-Based Designs

Distributed neuro-adaptive Time-Varying Formation (TVF) control for multi-agent systems with matching unknown nonlinearities is considered. According to different perspectives of the dynamical coupling strengths between the agents, two control strategies, named node- and edge-based, are designed and analyzed in the framework of Lyapunov theory, respectively. With the help of neural networks and nonsmooth analysis, both controllers guarantee the robust asymptotical convergence of the TVF errors and can also resist unknown matching disturbances. Node-based design is found to be fully-distributed, which does not depend on any global information, meanwhile the edge-based design is applicable for TVF on switching graphs. Some numerical simulations are provided to support the theoretical results.