Advanced Frozen Intelligent Control System of PMSM Optimized by Cerebellar Model Articulation Controller

Abstract

For permanent magnet synchronous motor speed and rotor position easily affected by the mechanical sensor signal transmission precision, to improve the performance of permanent magnet synchronous motor drive, the speed control system satisfies the requirement of fast response, and the complicated condition of frequent load disturbance has stronger resistance, this paper designed a small nerve network optimization of permanent magnet synchronous motor intelligent control system. The intelligent control system will be small neural networks applied to the model reference adaptive control of permanent magnet synchronous motor speed control system. On this basis, the structures, permanent magnet synchronous motor control system simulation, the simulation results show the system can accurately measure the rotational speed, rotor position and compared with the traditional model reference adaptive control, motor start-up speed no overshoot, has the stronger ability to resist load disturbance and load disturbance after speed restore faster (6 ms), in the motor control has strong practical application value.