the effects of faults can be expressed in linear-fractionaltransformation (LFT) forms, a fault-tolerant control systems design problem is formulated and solved via a linear matrix inequality (LMI)-based synthesis approach.In order to recover the convexity of the design problem whilst considering the robust performance and robust stability against faults and uncertainties simultaneously, a constrained optimisation approach is used. The simulation results of a design example (a longitudinal motion flight control problem for an unmanned aircraft in the case of suffering battle damage on its wing ) show that robust stability and satisfactory performance have been achieved.

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The current conventional automatic fault location method of power communication network mainly realizes the identification of faulty branches by calculating node power parameters, which leads to poor location effects due to the lack of effective analysis of fault signal data. In this regard, the automatic fault location method of the store head communication network based on a machine learning algorithm is proposed. Firstly, the fault signal data are collected and pre-processed, specifically including data cleaning and data format conversion, and then the individual fault signal is used as the basis to differentiate the weight parameters of different abnormal degrees and combine with the state threshold to realize the judgment of the fault node interval location. In the experiments, the fault location performance of the proposed method is verified. The experimental results show that when the proposed method is used for fault location, the relative positioning error value of the method is small and has a high fault location accuracy.