Abstract：In this paper, a self-organizing probabilistic fuzzy neural network control method is used to improve the control performance of permanent magnet linear synchronous motor (PMLSM). Probabilistic fuzzy neural network (PFNN) can effectively to estimate of uncertainty factors in the system of, and compared with NN has strong robustness, but the structure is fixed, low membership degree of node control to the current system is poorer, difficult to adjust the system steady-state error in the process of dynamic, so this article on the basis of the adopted a self-organized probabilistic fuzzy neural network controller (SOPFNN). In the case of parameter learning, a structure learning algorithm is adopted to ensure that each node can play the maximum role in the control process and further improve the tracking performance of the system. Simulation results show that the self-organizing probabilistic fuzzy neural network control not only improves the position tracking performance of the system, but also improves the robustness of the system.
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2020, Vol. 21 
