Study on a recurrent functional link-based fuzzy neural network controller with improved particle swarm optimization

A recurrent functional link-based fuzzy neural network controller with improved particle swarm optimization is proposed to control the mover of a permanent-magnet synchronous motor (PMSM) servo drive to track periodic reference trajectories. First, a recurrent functional link-based fuzzy neural network is proposed to control the PMSM, and the connective weights of the recurrent functional link-base neural network, the mean value and standard deviation of Gaussian function are trained online by recurrent algorithm. Moreover, an improved particle swarm optimization (IPSO) is adopted in this study to adapt the learning rates to improve the learning capability and increase the speed of constringency. Finally, the control performance of the proposed method is verified by the simulated results.