Nonlinear Uncertainties Canceling in Multi-Agent Systems Enabled by Cooperative Adaptation

This paper deals with uncertainties problem in multi-agent systems with novel cooperative adaptation approach. Since uncertainties in multi-agent systems are interconnected, local agent often faces uncertainties not only from itself but also from neighbors. The proposed approach is that a local agent estimates uncertainties from itself and neighboring agents and then changes control strategy. The uncertainties or the equivalences of neighbors can be estimated based on their available outputs; thus, the local agent can adapt to them to cancel out these effects. Stability analysis is also derived that characterizes the transient and steady state performance of multi-agent system. The simulation presents the details of the proposed cooperative adaptation mechanism by compared typical cooperative control.