Stator Flux Based Model Reference Adaptive Observers for Sensorless Vector Control and Direct Voltage Control of Doubly-Fed Induction Generator

In this project, two stator flux-based Model Reference Adaptive Observers (SF-MRAOs) for estimation of rotor speed and position in stand-alone DFIG is proposed. The cross product of reference and estimated stator flux linkage vectors is fed as controller input in the existing method, thereby making the observer model non-linear. 

The first proposed method, which is based on notch filtering, offers a performance comparable to that of the existing method, while reducing the number of voltage and current sensors required. The second proposed method linearizes the error input to the controller, making the controller design straight-forward, and also leading to superior performance than the existing methods. 

The linearized SF-MRAO is shown to work successfully with good dynamic performance in vector control of stand-alone DFIG. The paper also shows that the proposed linearized SF-MRAO can be employed for obtaining the rotor current angle in direct voltage control of stand-alone DFIG. The proposed system is simulated in MATLAB/Simulink.

Keywords: Doubly-fed induction generator, model reference adaptive observer, notch filter, parameter sensitivity, position estimation, rotor current control, sensor less control, speed estimation, stator flux.