In order to restrain the bouncing of contacts in the permanent magnet circuit breaker (PMCB) during closing process and improve their mechanical and electrical life, an intelligent closed-loop adaptive control system is proposed in this paper. The real-time displacement of the moving iron core of the PMCB is detected by the displacement sensor to obtain the real-time speed. A simulation model for the TS fuzzy control algorithm and that for the RBF neural network control algorithm were created based on MATLAB software, which were combined with the microcontroller and the intelligent control unit of the PMCB for controlling the dynamic characteristics of the closing process of the PMCB. Finally, an experimental measurement platform was constructed to test the number of contacts bouncing and the end speed of the moving core under the two control strategies. The test results show that the RBF neural network (RBF-NN) control algorithm is obviously superior to the fuzzy control algorithm, which is of great significance for the optimization of the dynamic characteristics of the PMCB.