Open AccessMRAS‐based speed estimation of grid‐connected doubly fed induction machine drive
Author(s) -
Kumar Rahul,
Das Sukanta
Publication year - 2017
Publication title -
iet power electronics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.637
H-Index - 77
eISSN - 1755-4543
pISSN - 1755-4535
DOI - 10.1049/iet-pel.2016.0768
Subject(s) - mras , control theory (sociology) , stator , matlab , context (archaeology) , rotor (electric) , grid , computer science , dspace , adaptive system , dimension (graph theory) , torque , voltage , control engineering , engineering , induction motor , vector control , mathematics , physics , algorithm , artificial intelligence , pure mathematics , electrical engineering , biology , operating system , mechanical engineering , paleontology , geometry , control (management) , thermodynamics
This study presents a new model reference adaptive system (MRAS)‐based speed estimation strategy for a grid‐connected doubly fed induction machine (DFIM) drive. The reference and the adaptive models of the proposed MRAS utilise instantaneous and steady‐state values, respectively, of a fictitious quantity obtained as the difference between two fictitious ratios of rotor voltage to current along the d and q axes. The dimension of this fictitious quantity is ohm (Ω) and has no physical significance. The proposed formulation is free from flux estimation and independent of stator and rotor resistance variations. This new formulation shows stable performance in the regenerating mode of operation of DFIM. All the relevant studies, in this context, are done in MATLAB/Simulink. The simulation study is further validated with a dSPACE‐1104‐based DFIM laboratory prototype.