Complex-Valued Model Reference Adaptive Systems for Speed Estimation of Induction Motor

In this study, two novel complex-valued model reference adaptive systems (MRASs) based on rotor flux and stator current are performed for speed-sensorless control of squirrel cage induction motor (SCIM) and tested under different operating conditions for a wide speed range. Nowadays, the complex-valued methods have become popular and provided significant advantages in some important applications where the signal or system can be defined in the complex domain. The reasons why these MRAS types are selected are that these structures are suitable to be defined in the complex domain, do not require external flux estimator, and are two of the most popular MRAS types. Finally, satisfactory estimation performances for both novel complex-valued MRAS algorithms have been obtained under simulations.