Worst Case Learning for H ∞ Consensus for Heterogeneous Multiagent Systems: A Resource-Constrained Game Approach.
This article investigates heterogeneous high-order nonlinear multiagent systems (MASs) under an event-triggered mechanism (ETM). A reinforcement learning (RL)-based zero-sum game (ZSG) approach is employed to solve the robust consensus problem. To handle heterogeneity, unified-dimension state variables are constructed,...