Position Of Permanent Magnet Synchronous Motor Control Based On Fuzzy Neural Network

Because of its good control effect, small size, high ratio of torque and current, high power factor and low self-inertia, permanent magnet synchronous motor has been widely used in industrial robots, CNC machine tools and other control of high precision position.Firstly, the research situation and development prospect of the position control system of permanent magnet synchronous motor are analyzed briefly. Then the paper analyzes the mathematical model of permanent magnet synchronous motor, combining the analysis comparison of coordinate transformation of permanent magnet synchronous motor in the coordinate transformation and mathematical model of permanent magnet synchronous motor, the two-phase rotating coordinate system of the mathematical model of decoupling operation. Using the control method while id=0, the current electromagnetic torque is the maximum. Then, we established the position control system of permanent magnet synchronous motor three closed loop regulation.Both of speed loop and current loop used PI control system and we designed fuzzy neural network PID controller according to the system position error and error's rate of change. By comparing the simulation experiments, we know that the strategy of combining fuzzy neural network and PI control is accuracy and useful. Also, the strategy improves the position of the system tracking performance and the speed and stability of control systems.Based on the conventional fuzzy neural network, we put forward the compensation fuzzy neural network position controller. The experimental results verify the feasibility and superiority of compensatory fuzzy neural network control algorithm in permanent magnet synchronous motor position servo system.