An adaptive neural network(NN) control approach is presented for the tracking control problem of a class of nonlinear large-scale interconnected systems when its structure is expanded. The method needs to design the control laws and adaptive laws of the newly added subsystems without changing the decentralized control laws and adaptive laws of the original subsystems, so that all subsystems in the expanded system have good tracking performances. The approximation function of the NN and the Backstepping technique are used to design the decentralized control laws and adaptive laws of the newly added subsystems. It is proved by the Lyapunov theory that all signals in the closed-loop expanded system controlled by the proposed controllers are bounded, and the expanded system can track accurately. Simulation results show the effectiveness of the proposed method.