AC Drives demand robust motor design with rugged construction, low cost, high reliability in service, and simple maintenance. In modern power drives, Sensorless Induction motor drives are more popular than other drives. A speed sensor/encoder-based drive is costlier and requires more space in case more parallel units are coupled together in drive operation. To address these difficulties, speed sensorless drives are introduced without loss of efficiency and reliability. However, Sensorless speed drive requires advanced control techniques in which complex calculations are there due to the nonlinearity of IM. In the recent past, Machine model-based methods i.e., MRAS (Model reference adaptive systems) and ELO (Extended Luenberger observer) have been popularized due to ease of implementation compared to other techniques. In this work, improved MRAS and ELO models are implemented and verified using Simulink software. Then, the same is validated with the help of an FPGA (field programmable gate array) based Snetly real-time controller. The key improvements are achieved as follows: effective speed estimation, robust speed tracking, reduced speed estimation error, and robust stability which helps to enhance the transient and steady-state performance of the drive.