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Multiobjective fault detection and isolation for flexible air-breathing hypersonic vehicle

机译:柔性呼吸超音速飞行器多目标故障检测与隔离

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摘要

An application of the multiobjective fault detection and isolation (FDI) approach to an air-breathing hypersonic vehicle (HSV) longitudinal dynamics subject to disturbances is presented. Maintaining sustainable and safe flight of HSV is a challenging task due to its strong coupling effects, variable operating conditions and possible failures of system components. A common type of system faults for aircraft including HSV is the loss of effectiveness of its actuators and sensors. To detect and isolate multiple actuator/sensor failures, a faulty linear parameter-varying (LPV) model of HSV is derived by converting actuator/system component faults into equivalent sensor faults. Then a bank of LPV FDI observers is designed to track individual fault with minimum error and suppress the effects of disturbances and other fault signals. The simulation results based on the nonlinear flexible HSV model and a nominal LPV controller demonstrate the effectiveness of the fault estimation technique for HSV.
机译:提出了多目标故障检测与隔离(FDI)方法在遭受干扰的呼吸式超音速飞行器(HSV)纵向动力学中的应用。保持HSV可持续安全飞行是一项艰巨的任务,因为它具有强大的耦合效应,可变的运行条件以及系统组件可能出现的故障。包括HSV在内的飞机的常见系统故障类型是其执行器和传感器的有效性下降。为了检测和隔离多个执行器/传感器故障,通过将执行器/系统组件故障转换为等效的传感器故障,得出HSV的线性参数变化(LPV)模型。然后,设计了一组LPV FDI观测器,以最小的误差跟踪单个故障并抑制干扰和其他故障信号的影响。基于非线性柔性HSV模型和标称LPV控制器的仿真结果证明了HSV故障估计技术的有效性。

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