loading page

Assessment of a PLL-ASMO Position/Speed Estimator for Sensor-less Control of Rotor-Tied DFIG (RDFIG)
  • Mwana Wa Kalaga Mbukani,
  • Nkosinathi Gule
Mwana Wa Kalaga Mbukani
University of Pretoria

Corresponding Author:mwanawakalaga.mbukani@up.ac.za

Author Profile
Nkosinathi Gule
Stellenbosch University
Author Profile


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.
25 May 2022Submitted to The Journal of Engineering
25 May 2022Submission Checks Completed
25 May 2022Assigned to Editor
30 Jun 2022Reviewer(s) Assigned
11 Jul 2022Review(s) Completed, Editorial Evaluation Pending
30 Jul 2022Editorial Decision: Revise Major
06 Sep 20221st Revision Received
13 Sep 2022Submission Checks Completed
13 Sep 2022Assigned to Editor
16 Sep 2022Reviewer(s) Assigned
27 Sep 2022Review(s) Completed, Editorial Evaluation Pending
16 Oct 2022Editorial Decision: Revise Major
21 Oct 20222nd Revision Received
22 Oct 2022Submission Checks Completed
22 Oct 2022Assigned to Editor
24 Oct 2022Reviewer(s) Assigned
06 Dec 2022Review(s) Completed, Editorial Evaluation Pending
13 Jan 2023Editorial Decision: Revise Major
11 Feb 20233rd Revision Received
21 Feb 2023Submission Checks Completed
21 Feb 2023Assigned to Editor
03 Mar 2023Reviewer(s) Assigned
11 Mar 2023Review(s) Completed, Editorial Evaluation Pending