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A new adaptive time-delay positive feedback con-troller (ATPFC) is presented for a class of nonlinear time-delay systems. The proposed control scheme consists of a neural networks-based identification and a time-delay positive feedback controller. Two high-order neural networks (HONN) incorpo-rated with a special dynamic identification model are employed to identify the nonlinear system. Based on the identified model,local linearization compensation is used to deal with the un-known nonlinearity of the system. A time-delay-free inverse model of the linearized system and a desired reference model are utilized to constitute the feedback controller, which can lead the system output to track the trajectory of a reference model.Rigorous stability analysis for both the identification and the tracking error of the closcd-loop control system is provided by means of Lyapunov stability criterion. Simulation results are in-cluded to demonstrate the effectiveness of the proposed scheme.