Adaptive and distributed control of nonlinear and heterogeneous multi-agent systems

The tracking synchronization problem of multi-agent systems with unknown nonlinear and heterogeneous dynamics is studied. A feedback linearization approach is used with neural networks to compensate for the uncertainties caused by the unknown and nonlinear dynamics of agents. Using the Lyapunov theory, an adaptive distributed control scheme is designed, and verified through the secondary voltage control of the practical microgrids.