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Volume 11
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10.3390/pr11061690
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Article

Actuator FDI Scheme for a Wind Turbine Benchmark Using Sliding Mode Observers

by
Vicente Borja-Jaimes
1,
Manuel Adam-Medina
1,*,
Jarniel García-Morales
1,
Gerardo Vicente Guerrero-Ramírez
1,
Betty Yolanda López-Zapata
2 and
Eduardo Mael Sánchez-Coronado
3
1
Electronic Engineering Department, TecNm/National Center for Research and Technological Development (CENIDET), Cuernavaca, Morelos 62490, Mexico
2
Department of Mechatronic Engineering, Polytechnic University of Chiapas, Tuxtla Gutierrez, Chiapas 29082, Mexico
3
Department of Mechatronic Engineering, Technological University of the Center of Veracruz, Cuitlahuac, Veracruz 94910, Mexico
*
Author to whom correspondence should be addressed.
Processes 2023, 11(6), 1690; https://doi.org/10.3390/pr11061690
Submission received: 18 April 2023 / Revised: 21 May 2023 / Accepted: 25 May 2023 / Published: 1 June 2023
(This article belongs to the Special Issue Innovative Techniques for Safety, Reliability, and Security in Control Systems)
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Abstract

This paper proposes a fault detection and isolation (FDI) scheme for a wind turbines subject to actuator faults in both the pitch system and the drive train system. The proposed scheme addresses fault detection and isolation problems using a fault estimation approach. The proposed approach considers the use of a particular class of sliding mode observers (SMOs) designed to maintain the sliding motion even in the presence of actuator faults. The fault detection problem is solved by reconstructing the actuator faults through an appropriate analysis of the nonlinear output error injection signal, which is required to keep the SMO in a sliding motion. To ensure accurate fault reconstruction, only two conditions are required, namely that the faults are bounded and they meet the matching condition. A scheme based on a bank of SMOs is proposed to solve the fault detection and isolation problem in the pitch system. For the drive train system, a scheme using only one SMO is proposed. The performance of the proposed FDI scheme is validated by using a wind turbine benchmark model subjected to several actuator faults. Normalized root mean square error (NRMSE) analysis is performed to evaluate the accuracy of the actuator fault estimations.
Keywords: fault detection and isolation (FDI); sliding mode observer (SMO); wind turbines fault detection and isolation (FDI); sliding mode observer (SMO); wind turbines

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MDPI and ACS Style

Borja-Jaimes, V.; Adam-Medina, M.; García-Morales, J.; Guerrero-Ramírez, G.V.; López-Zapata, B.Y.; Sánchez-Coronado, E.M. Actuator FDI Scheme for a Wind Turbine Benchmark Using Sliding Mode Observers. Processes 2023, 11, 1690. https://doi.org/10.3390/pr11061690

AMA Style

Borja-Jaimes V, Adam-Medina M, García-Morales J, Guerrero-Ramírez GV, López-Zapata BY, Sánchez-Coronado EM. Actuator FDI Scheme for a Wind Turbine Benchmark Using Sliding Mode Observers. Processes. 2023; 11(6):1690. https://doi.org/10.3390/pr11061690

Chicago/Turabian Style

Borja-Jaimes, Vicente, Manuel Adam-Medina, Jarniel García-Morales, Gerardo Vicente Guerrero-Ramírez, Betty Yolanda López-Zapata, and Eduardo Mael Sánchez-Coronado. 2023. "Actuator FDI Scheme for a Wind Turbine Benchmark Using Sliding Mode Observers" Processes 11, no. 6: 1690. https://doi.org/10.3390/pr11061690

APA Style

Borja-Jaimes, V., Adam-Medina, M., García-Morales, J., Guerrero-Ramírez, G. V., López-Zapata, B. Y., & Sánchez-Coronado, E. M. (2023). Actuator FDI Scheme for a Wind Turbine Benchmark Using Sliding Mode Observers. Processes, 11(6), 1690. https://doi.org/10.3390/pr11061690

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