An SMC-MRAS Speed Estimator for Sensor-Less Control of DFIG Systems in Wind Turbine Applications

Mwana Wa Kalaga Mbukani (), Michael Njoroge Gitau and Raj Naidoo
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Mwana Wa Kalaga Mbukani: Department of Electrical, Electronic and Computer Engineering, University of Pretoria, Pretoria 0002, South Africa
Michael Njoroge Gitau: Department of Electrical, Electronic and Computer Engineering, University of Pretoria, Pretoria 0002, South Africa
Raj Naidoo: Department of Electrical, Electronic and Computer Engineering, University of Pretoria, Pretoria 0002, South Africa

Energies, 2023, vol. 16, issue 6, 1-15

Abstract: A sliding mode control-based model reference adaptive system (SMC-MRAS) estimator for sensor-less control of doubly fed induction generator (DFIG) systems in wind turbine applications is proposed in this paper. The proposed SMC-MRAS estimator uses the rotor current as a variable of interest. The proposed SMC-MRAS estimator has the advantage of being immune to machine parameter variations. The SMC parameters are designed using the Lyapunov stability criteria. The performance of the proposed SMC-MRAS estimator is validated using simulations in MATLAB/SIMULINK. A comparative study between the proposed SMC-MRAS estimator and the PI-MRAS estimator is also conducted to demonstrate the superiority of the proposed SMC-MRAS estimator.

Keywords: doubly fed induction generators; speed sensor-less control; sliding mode control; model reference adaptive systems; field-oriented control (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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