Robust Input-Output Decoupling Control for Induction Motors with Improved Stator Flux Estimator

A robust input-output decoupling control strategy via non-linear state feedback for stator flux and torque of induction motors (IM) is proposed. To achieve decoupling control, it is shown that the tracking dynamics with respect to the outputs (stator flux amplitude and electrical torque) is asymptotically stable at an admissible operating equilibrium. A real time recurrent learning (RTRL) algorithm based recurrent neural network (RNN) is employed for efficient stator flux measurement. Finally, simulation results are presented to reveal the practicality of the proposed controller