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Due to its great potential value in theory and application, synthesized power and frequency control strategies of nonlinear wind power generation systems, especially combining with intelligent control methods, have been a focus in the academe. A synthesized power and frequency control method based on fuzzy neural networks presents nonlinear systems in this paper. The controller parameters were designed to detect the power and frequency fluctuation, and adaptive updating method was introduced to estimate and tracking error. Fuzzy neural networks was used to adjust the system parameters and construct automated power and frequency control, and the tracking error compensation control force, which given by state estimation, was used to realize adaptive power and frequency control. This framework leaded to a simple structure, an accurate detection and a high robustness. The simulation results in a wind power generator control system showed that it could work well with high dynamic performance and control precision under the condition of system parameters' variation and load torque disturbance.