The problem of enhancing the robust performance of nonlinear fault estimation (FE) is addressed by proposing a novel real-time gain-scheduling mechanism for discrete-time Takagi–Sugeno fuzzy systems. The real-time status of the operating point for the considered nonlinear plant is characterized by using these available normalized fuzzy weighting functions at both the current and the past instants of time. To achieve this, the developed fuzzy real-time gain-scheduling mechanism produces different switching modes by introducing key tunable parameters. Thus, a pair of exclusive FE gain matrices is designed for each switching mode on the strength of time-varying balanced matrices developed in this study, respectively. Since the implementation of more FE gain matrices can be scheduled according to the real-time status of the operating point at each sampling instant, the robust performance of nonlinear FE will be enhanced over the previous methods to a great extent. Finally, considerable numerical comparisons are implemented in order to illustrate that the proposed method is much superior to those existing ones reported in the literature.

中文翻译：

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通过新的实时增益调度机制增强离散时间非线性系统的模糊故障估计


通过为离散时间 Takagi-Sugeno 模糊系统提出一种新颖的实时增益调度机制，解决了增强非线性故障估计 (FE) 鲁棒性能的问题。通过在当前和过去时刻使用这些可用的归一化模糊加权函数来表征所考虑的非线性设备的操作点的实时状态。为了实现这一目标，所开发的模糊实时增益调度机制通过引入关键的可调参数来产生不同的切换模式。因此，根据本研究开发的时变平衡矩阵，分别为每种开关模式设计了一对专有的有限元增益矩阵。由于可以根据每个采样时刻工作点的实时状态来调度更多有限元增益矩阵的实现，因此非线性有限元的鲁棒性将比以前的方法得到很大程度的增强。最后，进行了大量的数值比较，以说明所提出的方法远远优于文献中报道的现有方法。