Search

In this paper, a new adaptive control method is presented for a class of induction motors. The dynamics of the system are assumed to be unknown and also are perturbed by some disturbances such as variation of load torque and rotor resistance. A type-2 fuzzy system based on rough neural network (T2FRNN) is proposed to estimate uncertainties. The parameters of T2FRNN are adjusted based on the adaptation laws which are obtained from Lyaponuv stability analysis. The effects of the uncertainties and the approximation errors are compensated by the proposed control method. Simulation results verify the good performance of the proposed control method. Also a numerical comparison is provided to show the effectiveness of the proposed fuzzy system. [ABSTRACT FROM AUTHOR]

In this study, a new adaptive controller is introduced for the induction motors (IMs) based on immersion and invariance (I&I) technique. The dynamics of the IM system are perturbed by some disturbances such as time‐varying rotor resistance and load torque. Accordingly, an adaptive controller is designed and the uncertain parameters are online estimated. The adaptation laws are obtained from the stability analysis based on I&I method. The simulation results verified the effectiveness of the proposed control method. It is revealed that the outputs of the IM could track the desired signals in the presence of the mentioned disturbances. Also, the results are compared with the conventional control methods and it is concluded that the proposed control approach resulted in better performance. [ABSTRACT FROM AUTHOR]