Adaptive Luenberger-Sliding Mode Controller Based Speed Estimation and Control of Sensorless Induction Motor

Abstract

In the last decade, different techniques of induction motor control were widely used for low and high-performance applications. For high-performance drive systems, the field-oriented control (FOC) is more efficient when it integrates with advanced control techniques. The conventional field-oriented control uses a sensor for speed feedback to the controller. Convectional FOC is affected by the coupling effect between torque and flux component and sensitive for the unknown parameter variation. Sensor feedback error may affect the reliability and increase cost and controller design complexity. The proposed ALSMC control approach uses advanced speed controllers, indirect field-oriented control (IFOC) with sliding mode control (SMC) and adaptive Luenberger state observer to achieve high dynamic performance. The simulation throughout the documentation was implemented by using MATLAB/Simulink software. In this thesis, the speed, torque, and stator current responses with MRAC based PI controller and Adaptive Luenberger Sliding Mode Control (ALSMC) controller were compared and found that the proposed ALSMC based controller showed improved dynamic performance and better stabilization for load torque variation. The proposed adaptive Luenberger sliding mode control is better in overshot which is 0.426% and that of PI controller is 4.348%, and it has better settling time which is 0.5seconds and that of PI is 0.98 seconds.