Fault Tolerant Model Predictive Control of Wind Turbine Against Actuator Faults Using Laguerre Functions

Amir Tasdighi, M. Menhaj
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Abstract

The use of wind power, as a major source of renewable energy, has been growing worldwide in recent decades. A large number of wind turbine (WT) generators has been deployed on wind farms located at both land and sea areas to meet the ever increasing demand for alternative energy resources. In order to improve the efficiency and the reliability of WTs, advanced fault detection, diagnosis and accommodation plans are of great importance. This paper proposes a model predictive controller using Laguerre functions with the aim of designing a fault tolerant control scheme which ensures the reliable performance of wind turbine in case of fault occurrence in the WT's pitch and generator actuators. In addition, a model-based strategy relying on recursive least squares (RLS) algorithm is proposed for fault identification. We provide an analytical stability analysis of the controller through the Lyapunov function candidate. The accuracy and the efficiency of the proposed method is evaluated and compared with conventional controllers in two different scenarios, namely, in the presence of actuator faults and in a fault-free system.
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基于Laguerre函数的风力发电机执行器故障容错模型预测控制
近几十年来,风力发电作为可再生能源的主要来源,在全球范围内不断发展。为了满足日益增长的对替代能源的需求,大量的风力发电机已经部署在陆地和海上的风电场上。为了提高WTs的工作效率和可靠性,先进的故障检测、诊断和适应方案至关重要。本文提出了一种基于Laguerre函数的模型预测控制器,目的是设计一种容错控制方案,以保证风电机组的俯仰和发电机执行器在故障情况下的可靠运行。此外,提出了一种基于模型的基于递归最小二乘(RLS)算法的故障识别策略。通过Lyapunov候选函数对控制器进行了解析稳定性分析。在两种不同的情况下,即在执行器存在故障和在无故障系统中,评估了所提出方法的精度和效率,并与传统控制器进行了比较。
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