Abstract: Controllable linear synchronous motor (CELSM) has a problem when operating. A control system based on adaptive neuro-fuzzy inference system (ANFIS) is designed. According to the specific structure and operation principle of CELSM, the mathematical models of voltage equation, electromagnetic thrust equation and motion equation are derived. Since the mathematical model of CELSM has disturbance uncertainty, and fuzzy control is adopted because of its strong pertinence. The membership function and control rules of traditional fuzzy control are difficult to be adjusted automatically. fuzzy inference system (FIS) can be trained by adaptive neural fuzzy controller using sample set according to the selected error function. The hybrid learning algorithm is used in the training. The parameters of membership function are adjusted online and the automatic acquisition of fuzzy rules is realized. Using MATLAB software modeling and simulation, compared with RBF neural network control and PI control, the results show that ANFIS control has good stability, high precision, fast response speed, strong anti-interference ability and strong adaptability.