Fault tolerant control of wind turbines with an adaptive output feedback sliding mode controller

Azizi, Askar; Nourisola, Hamid; Shoja-Majidabad, Sajjad

doi:10.1016/j.renene.2018.11.106

Cited by 65 publications

(36 citation statements)

References 46 publications

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“…In [97], a perturbation observer was used to estimate time-varying external disturbances including grid faults, voltage dips, and intermittent wind power inputs, and a nonlinear adaptive control with compensation was used to enhance the fault ride-through capability for a full-rated converter wind turbine. In [98], an adaptive sliding mode tolerant controller with compensation was addressed to alleviate the fluctuations in rotor speed, generator speed, and generator power under faulty conditions in a 5MW wind turbine system. In [99], an adaptive tolerant control algorithm, with the aid of fault estimation, was presented for wind turbines subjected to effectiveness loss faults in pitch actuators.…”

Section: Active Resilient Controlmentioning

confidence: 99%

An Overview on Fault Diagnosis, Prognosis and Resilient Control for Wind Turbine Systems

2021

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Wind energy is contributing to more and more portions in the world energy market. However, one deterrent to even greater investment in wind energy is the considerable failure rate of turbines. In particular, large wind turbines are expensive, with less tolerance for system performance degradations, unscheduled system shut downs, and even system damages caused by various malfunctions or faults occurring in system components such as rotor blades, hydraulic systems, generator, electronic control units, electric systems, sensors, and so forth. As a result, there is a high demand to improve the operation reliability, availability, and productivity of wind turbine systems. It is thus paramount to detect and identify any kinds of abnormalities as early as possible, predict potential faults and the remaining useful life of the components, and implement resilient control and management for minimizing performance degradation and economic cost, and avoiding dangerous situations. During the last 20 years, interesting and intensive research results were reported on fault diagnosis, prognosis, and resilient control techniques for wind turbine systems. This paper aims to provide a state-of-the-art overview on the existing fault diagnosis, prognosis, and resilient control methods and techniques for wind turbine systems, with particular attention on the results reported during the last decade. Finally, an overlook on the future development of the fault diagnosis, prognosis, and resilient control techniques for wind turbine systems is presented.

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Section: Active Resilient Controlmentioning

confidence: 99%

An Overview on Fault Diagnosis, Prognosis and Resilient Control for Wind Turbine Systems

2021

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“…Grave concern for the risks associated with faults, especially those affecting safety, reliability, and performance, has made the fault-tolerant control (FTC) an indispensable part of the robotic system design process which can enhance system reliability and ensure the effectiveness of the control system in the presence of unexpected faults [1]. Successful implementation of this approach to various applications has proven its effectiveness in diverse fields such as spacecrafts [2,3], robotics, [4,5,6,7] and energy [8,9,10]. In general, FTC can be categorized into two types, passive FTC (PFTC) and active FTC (AFTC).…”

Section: Introductionmentioning

confidence: 99%

Active fault-tolerant control of a Schon̈flies parallel manipulator based on time delay estimation

2021

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In this paper, a new hybrid fault-tolerant control (FTC) strategy based on nonsingular fast integral-type terminal sliding mode (NFITSM) and time delay estimation (TDE) is proposed for a Schönflies parallel manipulator. In order to detect, isolate, and accommodate actuator faults, TDE is used as an online fault estimation algorithm. Stability analysis of the closed-loop system is performed using Lyapunov theory. The proposed controller performance is compared with conventional sliding mode and feedback linearization control methods. The obtained results reveal the superiority of the proposed FTC based on TDE and NFITSM.

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“…The maximum power point tracking (MPPT) and reduction of mechanical load are two important research directions in WT. 2…”

Section: Introductionmentioning

confidence: 99%

Sensorless intelligent second-order integral sliding mode maximum power point tracking control for wind turbine system based on wind speed estimation

Xiao

Yang

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part I:

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Aiming at the maximum power point tracking for wind turbine, a sensorless intelligent second-order integral sliding mode control based on wind speed estimation is proposed in this article. The maximum wind energy capture is realized by controlling permanent magnet synchronous motor to adjust the speed of wind turbine. First, an intelligent second-order integral sliding mode control is designed for the speed loop and current loop control, which has fast convergence speed, strong robustness and can effectively reduce chattering. Second, a novel cascade observer based on direct sliding mode observer and extended high-gain observer is used to estimate the rotor speed and position. Besides, combined radial basis function neural network is used to estimate the valid value of wind speed. Both simulation and experiment are implemented, which verify the effectiveness of the proposed strategy under the condition of considering both model uncertainty and external disturbance.

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Fault tolerant control of wind turbines with an adaptive output feedback sliding mode controller

Cited by 65 publications

References 46 publications

An Overview on Fault Diagnosis, Prognosis and Resilient Control for Wind Turbine Systems

An Overview on Fault Diagnosis, Prognosis and Resilient Control for Wind Turbine Systems

Active fault-tolerant control of a Schon̈flies parallel manipulator based on time delay estimation

Sensorless intelligent second-order integral sliding mode maximum power point tracking control for wind turbine system based on wind speed estimation

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