Neuro-fuzzy adaptive control of the IM drive with elastic coupling

The paper deals with two concepts of a model reference adaptive control (MRAC) of the induction motor drive with elastic joint. The adaptive speed controller uses fuzzy neural network equipped with additional option for on-line tuning its chosen parameters. In the paper PI-type and sliding-mode fuzzy logic controllers are used as the speed controllers, whose connective weights are trained on-line according to the error between the state variable of the plant and the reference model. The torsional vibrations dumping abilities of the two-mass drive system with the field oriented control of induction motor are tested and compared for both analyzed neuro-fuzzy adaptive controllers. It is shown that torsional oscillations can be successfully suppressed in the proposed control structures, using only one basic feedback from the motor speed. The simulation results are verified in experimental tests, in the wide range of motor speed and parameters changes.