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Diagnosis of a solar power plant using TS fuzzy-based multimodel approach

机译:基于TS模糊的多模型方法的诊断太阳能发电厂

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In the context of the electricity production, the solar energy is appropriate and endless. At present the technologies of solar concentration are the one which present most possibilities for commercial use. Thus, it is necessary not only to design processes of conversion of energy, but it is also important to assure an availability of these equipment by the conception of fault detection and isolation (FDI) systems. To improve the behavior of the solar power plant, we use a model based on differential algebraic equations to describe variations of the solar radiation, ambient temperature, flow rate and temperature of fluid. These phenomena are highly nonlinear. Moreover, a large class of nonlinear systems can be well approximated by T-S fuzzy models. The diagnosis scheme is based on a fuzzy observer to estimate faults and faulty system states; a proportional (P) observer to estimate constant faults in then adopted. Using descriptor redundancy property, a solution is proposed in terms of linear matrix inequalities (LMI). The performance of the proposed approach is pointed out by focusing on a model of solar power plant through numerical results.
机译:在电力生产的背景下,太阳能是合适的,无穷无尽。目前太阳能浓度技术是对商业用途的大多数可能性的技术。因此,不仅需要对能量转换的设计过程,而且通过故障检测和隔离(FDI)系统的概念来确保这些设备的可用性也很重要。为了提高太阳能发电厂的行为,我们使用基于差分代数方程的模型来描述太阳辐射,环境温度,流体温度和流体温度的变化。这些现象非常非线性。此外,通过T-S模糊模型可以很好地近似大类非线性系统。诊断方案基于模糊观察者来估计故障和故障系统状态;采用比例(P)观察者以估计持续断层的采用。使用描述符冗余属性,以线性矩阵不等式(LMI)提出了解决方案。通过数值结果专注于太阳能发电厂的模型来指出所提出的方法的性能。

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