A recurrent wavelet neural network controller with improved particle swarm optimization for linear synchronous motor drive

A recurrent wavelet neural network (RWNN) controller is proposed in this study to control the mover of a permanent magnet linear synchronous motor (PMLSM) servo drive to track periodic reference trajectories. First, the dynamic model of the PMLSM drive system is derived. Next, an RWNN controller is proposed to control the PMLSM. Moreover, the connective weights, translations and dilations of the RWNN are trained online by back-propagation (BP) method. Furthermore, an improved particle swarm optimization (IPSO) is adopted to adapt the learning rates of the RWNN to improve the learning capability. Finally, the control performance of the proposed RWNN controller with IPSO is verified by some experimental results.