Robust control of uncertain nonlinear composite systems based on dynamic neural networks

The problem of tracking control is discussed for a class of uncertain nonlinear composite system based on dynamic neural networks. The tracking error and other signals are uniformly ultimately bounded by Lyapunov stable theory, and the controller derived is smooth. No a priori knowledge of an upper bound on "optimal" weights modeling errors and external disturbances is required.