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Assessment of a PLL-ASMO Position/Speed Estimator for Sensor-less Control of Rotor-Tied DFIG (RDFIG)

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In this paper, an adaptive sliding mode observer (ASMO) associated with a phase locked loop (PLL) is assessed for the sensor-less control of a rotor-tied doubly-fed induction generator (RDFIG). In the proposed PLL-ASMO estimator, the ASMO utilizes the stator current, the stator voltage and the back electromotive force (EMF) as state variables. The proposed ASMO is used in order to estimate the back-EMF from which the slip position/speed is extracted using a PLL. The design of the ASMO gains is based on the Lyapunov stability criteria to ensure the convergence of the proposed observer in a finite time. Therefore, the main contribution of this paper is to propose a PLL-based ASMO estimator that aims to improve the estimation by reducing the chattering effect. A comparative study between the standard PLL-SMO estimator and the ASMO-PLL estimator is presented. Also, For the first time, an adaptive sliding mode observer is used for the sensor-less control of a RDFIG. The performance of the proposed sensor-less control strategy is validated through simulation and experimental measurements under various operating conditions. Furthermore, the estimator is shown to be robust to machine parameter variation.
Title: Assessment of a PLL-ASMO Position/Speed Estimator for Sensor-less Control of Rotor-Tied DFIG (RDFIG)
Description:
In this paper, an adaptive sliding mode observer (ASMO) associated with a phase locked loop (PLL) is assessed for the sensor-less control of a rotor-tied doubly-fed induction generator (RDFIG).
In the proposed PLL-ASMO estimator, the ASMO utilizes the stator current, the stator voltage and the back electromotive force (EMF) as state variables.
The proposed ASMO is used in order to estimate the back-EMF from which the slip position/speed is extracted using a PLL.
The design of the ASMO gains is based on the Lyapunov stability criteria to ensure the convergence of the proposed observer in a finite time.
Therefore, the main contribution of this paper is to propose a PLL-based ASMO estimator that aims to improve the estimation by reducing the chattering effect.
A comparative study between the standard PLL-SMO estimator and the ASMO-PLL estimator is presented.
Also, For the first time, an adaptive sliding mode observer is used for the sensor-less control of a RDFIG.
The performance of the proposed sensor-less control strategy is validated through simulation and experimental measurements under various operating conditions.
Furthermore, the estimator is shown to be robust to machine parameter variation.

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