Approximation-free design for distributed consensus tracking of networked uncertain non-linear multi-agent systems with heterogenous high powers

This study investigates a distributed approximation-free design problem for guaranteed consensus tracking quality of networked uncertain heterogenous power-chained multi-agent systems with completely unknown non-linearities. Compared with the existing studies in the presence of power-chained state variables, the main contribution of this study is to provide a distributed low-complexity consensus tracker design strategy using only the relative output information among agents, without the use of adaptive neural or fuzzy function approximators for estimating unknown non-linear functions. A novel recursive design strategy independent of the feedback domination technique is established to deal with power-chained state variables under directed networks. Using the Lyapunov stability theorem, it is shown that the preselected performance of the consensus tracking error is ensured.