Research on PMSM servo control system based on MFNN

Permanent-magnet synchronous-motor is a multi-variable, non-linear strong coupling system that is highly sensitive to the outer interfere and inter perturbation. To improve the system robustness and PMSM Servo System Realtime, the advantages of fuzzy system and neural network are taken to establish a kind of improved fuzzy neural net-work (FNN) models and algorithm, which is used to speed controller of PMSM Servo System. An improved learning algorithm with the modified fuzzy weight is proposed on the basis of the fuzzy neurons model for the max-min fuzzy operator. The amount of calculation for the improved FNN model is reduced greatly and the convergence velocity is improved. By comparative study simulation of PID control, FNN control, and MFNN control, Simulation results show that the Servo System based on MFNN control with high robustness and steady precision was improved under the same conditions.