Distributed Adaptive Tracking Control for Unknown Nonlinear Networked Systems

In this paper, we investigate the cooperative tracking problem for a class of nonlinear uncertain networked systems subject to an active leader, whose state can merely be partially measured and input channel is disturbed as well. By virtue of neural network (NN) technique, the dynamics of followers are properly modeled on certain basis functions and their input channels are assumed to be disturbed as well. In this work, an observer-based adaptive control is proposed for the nonlinear networked systems which may have non-identical dynamics. It is shown via Lyapunov theory that the overall system is cooperatively uniformly ultimately bounded (UUB) by appropriately choosing the parameters under some graph condition. In the end, several numerical simulations are elaborated for validation of the proposed adaptive controller.