The hybrid recurrent fuzzy neural network (HRFNN) control for permanent magnet synchronous motor (PMSM) drive system\r\nusing rotor flux estimator is developed to control electric scooter in this paper. First, the dynamic models of a PMSM drive system\r\nwere derived in according to electric scooter.Owing to the load of electric scooter exited many uncertainties, for example, nonlinear\r\nfriction force of the transmission belt, and so forth. The electric scooter with nonlinear uncertainties made the PI controller to\r\ndisable speed tracking control. Moreover, in order to reduce interference of encoder and cost down, an HRFNN control system\r\nusing rotor flux estimator was developed to control PMSM drive system in order to drive electric scooter. The rotor flux estimator\r\nconsists of the estimation algorithm of rotor flux position and speed based on the back electromagnetic force (EMF) in order to\r\nsupply with HRFNN controller. The HRFNN controller consists of the supervisor control, RFNN, and compensated control with\r\nadaptive law is applied to PMSM drive system. The parameters of RFNN are trained according to different speeds in electric scooter.\r\nThe electric scooter is operated to provide disturbance torque. To show the effectiveness of the proposed controller, comparative\r\nstudies with PI controller are demonstrated by experimental results.
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