A New RF-MRAS Based Rotor Resistance Estimator Independent of Stator Resistance for Vector Controlled Induction Motor Drives

In this paper, a new MRAS based rotor resistance estimator independent of stator resistance is proposed for Indirect Field Oriented Controlled (IFOC) IM drives. Rotor Flux based MRAS Model Reference Adaptive System (RF-MRAS) for Rr estimation is gaining popularity for its simplicity in IFOC IM drives. In this scheme, the voltage model equations are used as the reference model. The voltage model equations in turn depend on stator resistance which varies with temperature during motor operation and more predominant at low frequencies/speed. This leads to performance deterioration of MRAS based rotor resistance estimation. Hence separate on-line estimator is required to track the stator resistance variation. The newly developed MRAS technique uses a robust Single Neuron Cascaded Neural Network (SNC-NN) based rotor flux estimator trained from input/output data including Rs changes. This is used as a reference model in the place of the conventional voltage model in RF-MRAS to form a novel stator resistance independent RF-MRAS for Rr estimation. The performance of proposed novel Rr estimation scheme is extensively investigated for various changes in Rr. The robustness of the proposed Rr estimator is extensively demonstrated through MATLAB simulations and compared with the conventional RF-MRAS. The performance enhancement of IFOC IM drive with proposed Rr estimation scheme over the conventional scheme is illustrated.