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

机译:基于TS模糊多模型方法的太阳能电站诊断。

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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:在发电方面,太阳能是适当而无穷的。目前,太阳能聚光技术是目前商业用途最广泛的一种技术。因此,不仅需要设计能量转换过程,而且还必须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。为了改善太阳能发电厂的性能,我们使用基于微分代数方程的模型来描述太阳辐射,环境温度,流速和流体温度的变化。这些现象是高度非线性的。此外,通过T-S模糊模型可以很好地近似一类非线性系统。该诊断方案基于模糊观测器来估计故障和故障系统状态。然后采用比例(P)观测器来估计恒定故障。利用描述符冗余属性,提出了一种关于线性矩阵不等式(LMI)的解决方案。通过数值结果,重点研究了太阳能发电厂的模型,指出了该方法的性能。

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