PMLSM recurrent neural network compensation simulation study

The driven system by permanent magnet linear synchronous motor has the characteristics of zero mechanical damping and weak anti-disturbance. In order to restrain disturbance introduced by the parameter variation and external load of the PMLSM control system. Disturbance observer is used for compensation. Compensator is effective under small range of parameter variations and external load disturbance, not for great parameter variations. To increase the control performance of the PMLSM drive system under the occurrence of parameter variations and external load disturbance, a recurrent neural network compensator is proposed to replace a disturbance observer. The simulation results show the good performance for the system by using recurrent neural network to adjust the parameters of neural network on-line dynamically on the condition of variety of system parameter and the impact of external load.