Model Reference Adaptive System Based Precise Online Inertia Identification of Induction Motor with Error Utilization Technique

2022 ◽  
Vol 1 (1) ◽  
pp. 1
Author(s):  
Vinod Patel ◽  
Chirag Raval ◽  
Dr. P. N. Tekwani ◽  
Jay D. Mistry
2020 ◽  
Vol 5 (1) ◽  
pp. 199-213
Author(s):  
Soufien Hajji ◽  
Ramzi Ben Chehida ◽  
Hichem Zayani ◽  
Noomen Bouaziz ◽  
Youssef Agrebi Zorgani

AbstractThis article presents a new development of an indirect stator flux-oriented controller for sensorless speed induction motor drive utilising instantaneous and steady-state values, respectively, of a fictitious resistance symbolised as R_f. The dimension of the fictitious quantity, in this context, is the ohm, which is the difference between the stator d- and q-axis fictitious resistances. However, from the measurement of the stator voltage and currents of the machine, two independent resistance estimators are built. Therefore, the first is considered as a reference model of the induction machine (IM), and the second is considered as an adjustable model. Subsequently, the error between the states of the two models is used to drive a suitable adaptation mechanism that generates the estimation of the speed, for the adjustable model. Furthermore, the structure of the proposed estimator is free from stator resistance and eliminates the requirement of any flux computation. All the detailed simulation study is carried out in MATLAB/Simulink to validate the proposed method and to highlight the robustness and the stability of the proposed model reference adaptive system estimator.


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