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Health-Management Driven Control Reconfiguration Approach for Flight Vehicles

机译:卫生管理驱动控制重新配置飞行车辆的重新配置方法

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A prognostic system makes it possible to anticipate loss of functionality before it occurs with sufficient lead time to take actions that mitigate the impact of this loss. We focus on the forms of mitigation within the flight vehicle that influence the operational dynamics but do not directly amend the mission plan. Thus, we focus upon the reconfiguration of the feedback control strategy for the flight system. The high degree of complexity in the design and dynamics of modern aircraft is typically handled using a hierarchical control scheme in which there are several levels of control at increasing levels of responsibility: the component level, the subsystem level, and the system level. Our reconfiguration strategy involves mitigating problems that are detected at the component level at both the level in which the fault is detected and higher levels as well. There are, thus, two subproblems to the reconfiguration: (a) an adaptive control problem at the lower level to extend component life and derive new component performance limits, and (b) a supervisory control problem at the higher level to adapt the system controller to maximize system capability while respecting the performance limitations. Since our reconfiguration occurs in the context of a dynamic system, we need to respect the stability implications of the reconfiguration. To address this, we apply bandwidth analyses at the component level and the systems level in a robust performance context. A conservative criterion for stability is to impose rate limits for reconfiguration that insure that undesired, and possibly unmodeled, modes of behavior are not driven by reconfiguration activities. For specific hardware, extensions beyond this conservative approach may be warranted (e.g. to catch faulty behavior) and validated on a case-by-case basis, essentially by extending the component modeling to include a model of behavior under certain types of reconfiguration.
机译:预后系统可以预测在发生足够的提前时间之前进行功能丧失,以采取减轻这种损失的影响的行动。我们专注于影响运营动态但不直接修改任务计划的飞行车内的减缓形式。因此,我们专注于重新配置飞行系统的反馈控制策略。现代飞机设计和动态的高度复杂程度通常使用分层控制方案来处理,其中在增加责任水平时有几个级别的控制:组件级别,子系统级别和系统级别。我们的重新配置策略涉及在检测到故障和更高水平的级别处在组件级别检测到的问题。因此,两个子问题到重新配置:(a)较低级别的自适应控制问题,以扩展分量寿命并导出新的组件性能限制,并且(b)在更高级别的监控问题以适应系统控制器在尊重性能限制的同时最大化系统功能。由于我们的重新配置发生在动态系统的上下文中,因此我们需要尊重重新配置的稳定性范围。为解决此问题,我们在稳健的性能上下文中应用组件级别和系统级别的带宽分析。保守稳定性的标准是施加重新配置的速率限制,以确保不希望的,并且可能是未拼接的,行为模式不是通过重新配置的动力的推动。对于特定的硬件,可以保证这种保守方法的扩展(例如,以捕获故障行为)并根据逐个案例验证,基本上通过扩展组件建模来包括在某些类型的重新配置下包括行为模型。

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