Research On Permanent Magnet Synchronous Motor Control System Based On Fuzzy RBF Neural Network

With the continuous improvement of industrial automation and the convenience of life,in the fields of industrial automation,manufacturing industry,automobiles,home appliances,etc.,permanent magnet synchronous motors have developed rapidly and are more and more widely used.Compared with electric excitation motors,PMSM has the advantages of simple structure,high power saving efficiency and reliable operation.At present,the PMSM control method commonly used in the field of simpler and less demanding industrial control automation is still the traditional PID control,which is characterized by a simple algorithm structure,reliable operation and less application difficulty,but in the face of a complex operating environment As well as some high-performance motor control,the weaknesses of traditional PID control appear.For example,in the case of large fluctuations in load torque or high requirements on the control accuracy of the motor output speed,traditional PID control cannot achieve the required control effect and cannot meet the PMSM control requirements.In order to make the PMSM control system have better control accuracy and effect,this paper is based on the permanent magnet synchronous motor vector control system,on the basis of which combines the advantages of fuzzy control and radial basis function(RBF)neural network,By controlling the parameters of the PID controller,the purpose of optimizing the PMSM vector control system is achieved.The controller uses the RBF neural network algorithm to identify the motor parameters of the permanent magnet synchronous motor vector control system online.Through the optimized control of the fuzzy RBF neural network PID controller,the impact of environmental changes during PMSM operation is reduced.To achieve the purpose of fast control response,smooth operation and precision.The controller overcomes the shortcomings of the traditional PID controller with fixed parameters and fuzzy PID control that relies too much on the practical experience of experts or operators.This article first introduces the mathematical model of PMSM under three different axis systems and the principle of coordinate transformation,and explains the principle of vector control technology and space vector pulse width modulation(SVPWM)technology.Then it analyzes the composition of the vector control system of permanent magnet synchronous motor,and then conducts the research,simulation and comparison of traditional PID,fuzzy PID and fuzzy RBF neural network control on the basis of it.Through theoretical analysis,the simulation models of various controllers were built in MATLAB software using simulink simulation tools,and combined with the PMSM vector control system,the operation simulation of PMSM no-load start and sudden load was carried out The analysis proves the effectiveness and feasibility of fuzzy RBF neural network control applied in the PMSMvector control system.The controller makes the PMSM control system more adaptive and anti-jamming.