Model Predictive Current Control of Induction Motor Drive Integrated with Inverse Rotor Time Constant Estimator

In induction motor (IM) drives, rotor resistance tends to vary significantly due to temperature changes during prolonged operation of drives. Rotor resistance variation can degrade the motor performance, making it crucial to accurately estimate the rotor resistance/rotor time constant to maintain optimal control and achieve high-performance operation. Nowadays, model predictive control (MPC) has gained significant popularity due to its rapid dynamic response and precise control capabilities over the indirect rotor field-oriented control (IRFOC) of IM drives. In this work, a robust model predictive current control (MPCC) scheme for IM drive integrated with inverse rotor time constant estimator has been designed. However, similar to IRFOC, the MPCC scheme is also limited by its dependency on the rotor resistance of the machine, which affects the accuracy of the calculation of slip speed. Thus, in the proposed work, a reactive power (Q) based model reference adaptive system (MRAS) has been incorporated with MPCC scheme to estimate the inverse rotor time constant <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$(f_{r})$</tex>, which makes the MPCC scheme robust against the parameter variation. The proposed work for <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$f_{\gamma}$</tex> estimation approach ensures precise current control and quicker responses to variations in <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$f_{r}$</tex> as compared to the IRFOC. The effectiveness of the proposed MPCC algorithm integrated with an inverse rotor time constant estimator for estimation of inverse rotor time constant in both motoring and generating modes of operation is validated through simulation in MATLAB®/Simulink.