The hybrid RFNN control for a PMSM drive electric scooter using rotor flux estimator

Abstract

The hybrid recurrent fuzzy neural network (HRFNN) control permanent magnet synchronous motor (PMSM) drive system using rotor flux estimator is developed for controlling electric scooter in order to raise robustness and reduce interference and cost of encoder in this paper. First, the dynamic models of a PMSM drive system were derived in according to electric scooter. The proportional integral (PI) controller used for speed controller cannot able to process for the electric scooter due to existence of nonlinear uncertainty. The HRFNN control system using rotor flux estimator was developed to control electric scooter driven by PMSM in order to conquer disadvantage for PI controller and reduce interference and cost of encoder. The rotor flux estimator consists of the estimation algorithm of rotor flux position and speed based on the back electromagnetic force (EMF) to provide the feedback signal for HRFNN control system. The HRFNN control system consists of the supervisor control, the RFNN and the compensated control with adaptive law. To show the effectiveness of the proposed controller, comparative studies with PI controller are demonstrated by experimental results. © 2013 Elsevier Ltd.