The invention discloses a fuzzy neural network control method for an active electric power filter. According to the method, self-adaptation control, RBF (Radial Basis Function) neural network control and fuzzy neural network control are combined. When the method is applied, firstly, a mathematic model of the active electric power filter with disturbance and error is established, and secondly, a fuzzy neural network controller is obtained based on design of a self-adaptation RBF neural network. According to the method, an instruction current is tracked in real time, the dynamic performance of a system is improved, the robustness of the system is improved, and the system is not sensitive to parameter change. Through design of the sliding mode variable structure system, the active electric power filter is ensured to operate along a sliding mode track, the uncertainty of the system can be overcome, the robustness to interference is very high, and the high control effect on a nonlinear system is realized. The nonlinear part in the active electric power filter is approximated by designing a self-adaptation RBF neural network controller. The instruction current can be tracked in real time and the robustness of the system is improved by designing the fuzzy neural network controller.