Aerodynamic Torque Estimation Techniques During Partial Load Operation of Wind Turbine Via Fuzzy Logic and Least Square Methods

Abdul Wahid A. Saif; Ali M. Al Misbah; Samir Al-Amer; Sami El Ferik

doi:10.1109/DeSE68208.2025.11367903

Aerodynamic Torque Estimation Techniques During Partial Load Operation of Wind Turbine Via Fuzzy Logic and Least Square Methods

Abdul Wahid A. Saif^*
, Ali M. Al Misbah
, Samir Al-Amer
, Sami El Ferik

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Wind energy is a promising renewable energy source. The study of fault estimation and tolerant control is based on a modeled wind turbine system. Due to the nonlinearity in the model that appears in the aerodynamic torque, different estimation techniques for aerodynamic torque are studied during partial load operation of the wind turbine. In this short paper, Takagi-Sugeno fuzzy model-based estimation, Recursive least squares-based estimation using forgetting factor (RLS-FF), Recursive least squares-based estimation using Kalman filter (RLS-KF), Recursive least squares-based estimation using normalized gradient (RLSNG), and Recursive least squares-based estimation using unnormalized gradient. (RLS-UNG) will be briefly described for the aerodynamic torque estimation during partial load operation of the wind turbine. Results showed that recursive least squares estimation based on the Kalman filter and recursive least squares estimation based on normalized gradient outperformed recursive least squares estimation based on forgetting factor and Takagi-Sugeno-based estimation.

Original language	English
Title of host publication	Proceedings - 18th International Conference on Developments in eSystems Engineering, DeSE 2025
Editors	Dhiya Al-Jumeily Obe, Sulaf Assi, Jamila Mustafina, Abir Hussain, Manoj Jayabalan, Roxana Radvan, Bogdan Bita, Hissam Tawfik, Neil Rowe
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	314-319
Number of pages	6
ISBN (Electronic)	9798331587659
DOIs	https://doi.org/10.1109/DeSE68208.2025.11367903
State	Published - 2025
Event	18th International Conference on Developments in eSystems Engineering, DeSE 2025 - Bucharest, Romania Duration: 10 Nov 2025 → 12 Nov 2025

Publication series

Name	Proceedings - 18th International Conference on Developments in eSystems Engineering, DeSE 2025

Conference

Conference	18th International Conference on Developments in eSystems Engineering, DeSE 2025
Country/Territory	Romania
City	Bucharest
Period	10/11/25 → 12/11/25

Bibliographical note

Publisher Copyright:
© 2025 IEEE.

Keywords

Aerodynamic Torque Estimation
Partial Load Operation
Recursive least squares method
Takagi-Sugeno fuzzy
Wind Turbine

ASJC Scopus subject areas

Artificial Intelligence
Computer Science Applications
Control and Systems Engineering
Health Informatics

Access to Document

10.1109/DeSE68208.2025.11367903

Cite this

Saif, A. W. A., Al Misbah, A. M., Al-Amer, S., & El Ferik, S. (2025). Aerodynamic Torque Estimation Techniques During Partial Load Operation of Wind Turbine Via Fuzzy Logic and Least Square Methods. In D. A.-J. Obe, S. Assi, J. Mustafina, A. Hussain, M. Jayabalan, R. Radvan, B. Bita, H. Tawfik, & N. Rowe (Eds.), Proceedings - 18th International Conference on Developments in eSystems Engineering, DeSE 2025 (pp. 314-319). (Proceedings - 18th International Conference on Developments in eSystems Engineering, DeSE 2025). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/DeSE68208.2025.11367903

Saif, Abdul Wahid A. ; Al Misbah, Ali M. ; Al-Amer, Samir et al. / Aerodynamic Torque Estimation Techniques During Partial Load Operation of Wind Turbine Via Fuzzy Logic and Least Square Methods. Proceedings - 18th International Conference on Developments in eSystems Engineering, DeSE 2025. editor / Dhiya Al-Jumeily Obe ; Sulaf Assi ; Jamila Mustafina ; Abir Hussain ; Manoj Jayabalan ; Roxana Radvan ; Bogdan Bita ; Hissam Tawfik ; Neil Rowe. Institute of Electrical and Electronics Engineers Inc., 2025. pp. 314-319 (Proceedings - 18th International Conference on Developments in eSystems Engineering, DeSE 2025).

@inproceedings{7f7d5741bea14a8b9046c5fd19143fbd,

title = "Aerodynamic Torque Estimation Techniques During Partial Load Operation of Wind Turbine Via Fuzzy Logic and Least Square Methods",

abstract = "Wind energy is a promising renewable energy source. The study of fault estimation and tolerant control is based on a modeled wind turbine system. Due to the nonlinearity in the model that appears in the aerodynamic torque, different estimation techniques for aerodynamic torque are studied during partial load operation of the wind turbine. In this short paper, Takagi-Sugeno fuzzy model-based estimation, Recursive least squares-based estimation using forgetting factor (RLS-FF), Recursive least squares-based estimation using Kalman filter (RLS-KF), Recursive least squares-based estimation using normalized gradient (RLSNG), and Recursive least squares-based estimation using unnormalized gradient. (RLS-UNG) will be briefly described for the aerodynamic torque estimation during partial load operation of the wind turbine. Results showed that recursive least squares estimation based on the Kalman filter and recursive least squares estimation based on normalized gradient outperformed recursive least squares estimation based on forgetting factor and Takagi-Sugeno-based estimation.",

keywords = "Aerodynamic Torque Estimation, Partial Load Operation, Recursive least squares method, Takagi-Sugeno fuzzy, Wind Turbine",

author = "Saif, \{Abdul Wahid A.\} and \{Al Misbah\}, \{Ali M.\} and Samir Al-Amer and \{El Ferik\}, Sami",

note = "Publisher Copyright: {\textcopyright} 2025 IEEE.; 18th International Conference on Developments in eSystems Engineering, DeSE 2025 ; Conference date: 10-11-2025 Through 12-11-2025",

year = "2025",

doi = "10.1109/DeSE68208.2025.11367903",

language = "English",

series = "Proceedings - 18th International Conference on Developments in eSystems Engineering, DeSE 2025",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "314--319",

editor = "Obe, \{Dhiya Al-Jumeily\} and Sulaf Assi and Jamila Mustafina and Abir Hussain and Manoj Jayabalan and Roxana Radvan and Bogdan Bita and Hissam Tawfik and Neil Rowe",

booktitle = "Proceedings - 18th International Conference on Developments in eSystems Engineering, DeSE 2025",

address = "United States",

}

Saif, AWA, Al Misbah, AM, Al-Amer, S & El Ferik, S 2025, Aerodynamic Torque Estimation Techniques During Partial Load Operation of Wind Turbine Via Fuzzy Logic and Least Square Methods. in DA-J Obe, S Assi, J Mustafina, A Hussain, M Jayabalan, R Radvan, B Bita, H Tawfik & N Rowe (eds), Proceedings - 18th International Conference on Developments in eSystems Engineering, DeSE 2025. Proceedings - 18th International Conference on Developments in eSystems Engineering, DeSE 2025, Institute of Electrical and Electronics Engineers Inc., pp. 314-319, 18th International Conference on Developments in eSystems Engineering, DeSE 2025, Bucharest, Romania, 10/11/25. https://doi.org/10.1109/DeSE68208.2025.11367903

Aerodynamic Torque Estimation Techniques During Partial Load Operation of Wind Turbine Via Fuzzy Logic and Least Square Methods. / Saif, Abdul Wahid A.; Al Misbah, Ali M.; Al-Amer, Samir et al.
Proceedings - 18th International Conference on Developments in eSystems Engineering, DeSE 2025. ed. / Dhiya Al-Jumeily Obe; Sulaf Assi; Jamila Mustafina; Abir Hussain; Manoj Jayabalan; Roxana Radvan; Bogdan Bita; Hissam Tawfik; Neil Rowe. Institute of Electrical and Electronics Engineers Inc., 2025. p. 314-319 (Proceedings - 18th International Conference on Developments in eSystems Engineering, DeSE 2025).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Aerodynamic Torque Estimation Techniques During Partial Load Operation of Wind Turbine Via Fuzzy Logic and Least Square Methods

AU - Saif, Abdul Wahid A.

AU - Al Misbah, Ali M.

AU - Al-Amer, Samir

AU - El Ferik, Sami

PY - 2025

Y1 - 2025

N2 - Wind energy is a promising renewable energy source. The study of fault estimation and tolerant control is based on a modeled wind turbine system. Due to the nonlinearity in the model that appears in the aerodynamic torque, different estimation techniques for aerodynamic torque are studied during partial load operation of the wind turbine. In this short paper, Takagi-Sugeno fuzzy model-based estimation, Recursive least squares-based estimation using forgetting factor (RLS-FF), Recursive least squares-based estimation using Kalman filter (RLS-KF), Recursive least squares-based estimation using normalized gradient (RLSNG), and Recursive least squares-based estimation using unnormalized gradient. (RLS-UNG) will be briefly described for the aerodynamic torque estimation during partial load operation of the wind turbine. Results showed that recursive least squares estimation based on the Kalman filter and recursive least squares estimation based on normalized gradient outperformed recursive least squares estimation based on forgetting factor and Takagi-Sugeno-based estimation.

AB - Wind energy is a promising renewable energy source. The study of fault estimation and tolerant control is based on a modeled wind turbine system. Due to the nonlinearity in the model that appears in the aerodynamic torque, different estimation techniques for aerodynamic torque are studied during partial load operation of the wind turbine. In this short paper, Takagi-Sugeno fuzzy model-based estimation, Recursive least squares-based estimation using forgetting factor (RLS-FF), Recursive least squares-based estimation using Kalman filter (RLS-KF), Recursive least squares-based estimation using normalized gradient (RLSNG), and Recursive least squares-based estimation using unnormalized gradient. (RLS-UNG) will be briefly described for the aerodynamic torque estimation during partial load operation of the wind turbine. Results showed that recursive least squares estimation based on the Kalman filter and recursive least squares estimation based on normalized gradient outperformed recursive least squares estimation based on forgetting factor and Takagi-Sugeno-based estimation.

KW - Aerodynamic Torque Estimation

KW - Partial Load Operation

KW - Recursive least squares method

KW - Takagi-Sugeno fuzzy

KW - Wind Turbine

UR - https://www.scopus.com/pages/publications/105034187574

U2 - 10.1109/DeSE68208.2025.11367903

DO - 10.1109/DeSE68208.2025.11367903

M3 - Conference contribution

AN - SCOPUS:105034187574

T3 - Proceedings - 18th International Conference on Developments in eSystems Engineering, DeSE 2025

SP - 314

EP - 319

BT - Proceedings - 18th International Conference on Developments in eSystems Engineering, DeSE 2025

A2 - Obe, Dhiya Al-Jumeily

A2 - Assi, Sulaf

A2 - Mustafina, Jamila

A2 - Hussain, Abir

A2 - Jayabalan, Manoj

A2 - Radvan, Roxana

A2 - Bita, Bogdan

A2 - Tawfik, Hissam

A2 - Rowe, Neil

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 18th International Conference on Developments in eSystems Engineering, DeSE 2025

Y2 - 10 November 2025 through 12 November 2025

ER -

Saif AWA, Al Misbah AM, Al-Amer S, El Ferik S. Aerodynamic Torque Estimation Techniques During Partial Load Operation of Wind Turbine Via Fuzzy Logic and Least Square Methods. In Obe DAJ, Assi S, Mustafina J, Hussain A, Jayabalan M, Radvan R, Bita B, Tawfik H, Rowe N, editors, Proceedings - 18th International Conference on Developments in eSystems Engineering, DeSE 2025. Institute of Electrical and Electronics Engineers Inc. 2025. p. 314-319. (Proceedings - 18th International Conference on Developments in eSystems Engineering, DeSE 2025). doi: 10.1109/DeSE68208.2025.11367903

Aerodynamic Torque Estimation Techniques During Partial Load Operation of Wind Turbine Via Fuzzy Logic and Least Square Methods

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

Fingerprint

Cite this