Combining with the characteristic of the fuzzy control and the neural network control(NNC), a new kind of the fuzzy neural network controller is proposed, and the synthesis design method of the control law and fast speed learning algorithm of the parameters of networks are put forward. The output of the controller is composed of two parts, part one is derived on basis of the principle of sliding control, the lower order model and the estimated parameters of the plant are only required, part two is derived on basis FNN, it is used to compensate the uncertainties of the systems. Because new type of FNN controller extracts from the advantages of the intelligent control and model based sliding mode control, the numbers of adjusting parameters and the structure of FNN are simplified at large, and the practical significance and variation range are attached to each layer of the network and its connected weights, the control performance and learning speed are increased at large. The lightness of the conclusions Combining with the characteristic of the fuzzy control and the neural network control (NNC), a new kind of the fuzzy neural network controller is proposed, and the synthesis design method of the control law and fast speed learning algorithm of the parameters of networks are put forward. The output of the controller is composed of two parts, part one is derived on basis of the principle of sliding control, the lower order model and the estimated parameters of the plant are only required, part two is derived on basis FNN, it is used to compensate the uncertainties of the systems. Because new type of FNN controller extracts from the advantages of the intelligent control and model based sliding mode control, the numbers of adjusting parameters and the structure of FNN are simplified at large, and the useful significance and variation range are attached to each layer of the network and its connected weights, the control performance and learning speed are increased at large. The lightness of the conclusions