The invention relates to a strict feedback system neural network control method based on lumped composite estimation, belongs to the field of intelligent control methods, and is used for solving the problem of unknown dynamic states and time-varying disturbance in an uncertain feedback system with external interference. The method is based on a frame of an inverse step method, and a neural networkis adopted to estimate a nonlinear function of the system; a disturbance observer is used for processing the composite disturbance formed by the neural network approximation error and the time-varying disturbance; by utilizing the neural network estimation and disturbance observation estimation of the online data, the lumped composite estimation error is constructed, and an updating law of the neural network and the disturbance observer is designed; and finally input is designed and controlled based on neural network estimation and disturbance observation estimation. According to the method,neural network learning and disturbance observation are organically combined, so that an effective way for processing the strict feedback system control with time-varying interference is provided.