Control Neuro-Fuzzy of a Dual Star Induction Machine (DSIM) supplied by Five-Level Inverter



This work relates to a hybrid scheme (Neuro-Fuzzy) for speed control of a dual star induction motor (DSIM) with enhanced
performance. A 4-layer network is utilized to set the Fuzzy elements in order to minimize error square. To control this machine,
two five-level inverters with PWM techniques are introduced and an indirect field oriented method is used. Simulation results
are presented for the NF controller; it is observed that the NFC gives better responses and robustness for the speed control
of this machine with its load disturbances and parameter variations, such as increased rotor resistance and moment of
inertia. The results are compared with results obtained from a conventional inverter. Notably, there is a great drop in the
stator currents, and the magnitude of the pulsating electromagnetic torque is reduced for a five-level inverter compared with
a conventional inverter.


Dual stars induction machine (DSIM), Indirect field oriented control (IFOC), five-level inverter, Neuro-fuzzy cntroller (NFC).

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