Advanced integrated Control and Monitoring of Actuation Systems

产品质量和可靠性仍然是制造商的首要任务之一，尽管需要降低成本，但必须保持这些。对设备供应商的要求越来越高，以确保他们生产的产品的质量和可靠性。先进的控制与先进的状态监测相结合越来越重要，并成为下一代产品不可或缺的组成部分。故障检测和诊断（FDD）和状态监测系统有助于提高系统制造或运行的可靠性。FDD系统在预防性非计划维护、生产线末端生产测试和潜在的高级控制方面的好处是巨大的，以补偿组件的退化。FDD策略可以基于模型，也可以基于信号。基于模型的策略非常有效，但用于可以进行数学建模的系统。对于没有或无法推导出有意义的数学模型的复杂系统，必须使用基于信号的策略。本文考虑了基于信号和基于模型的策略在驱动系统状态监测和故障诊断中的结合应用。状态监测将为先进的前馈鲁棒控制策略的自适应修改提供信息，以获得更好的性能和退化补偿。本文以航空航天领域的电-静液作动系统为研究对象。基于模型的状态监测使用估计策略。该建议中考虑的基于模型的策略将基于平滑变结构滤波器（SVSF）。SVSF是一种鲁棒滤波器，具有独特的适用于状态监测的特征；在性能和稳定性方面，它可以更好地适应系统中由于故障条件而产生的不确定性。通常，现实世界的系统根据许多不同的操作机制（或模式）运行。操作模式也可能暗示故障情况。一种能够跟踪动态系统模式变化的策略是交互多模型（IMM）概念。作为其实现的一部分，IMM需要一个评估策略。在本研究中，SVSF的一个新的衍生将与IMM相结合，以跟踪由于故障条件引起的变化，作为增强状态监测和鲁棒控制策略的一部分。对于不容易建模且具有周期性的故障条件，将使用基于信号的策略。状态监测的结果将输入到鲁棒滑模控制器中，该控制器将根据上述SVSF/IMM方法确定的驱动系统的模式调整其前馈项。控制输入的鲁棒细化与状态监测相结合，是致动行业的变革。

Product quality and reliability continue to be amongst the top priorities of manufacturers, and these must be maintained in spite of the need for lower costs. The demands placed on equipment suppliers to assure quality and reliability of the products they produce is increasing. Advanced control combined with advanced condition monitoring are increasingly important and are becoming integral and essential elements of next generation products. Fault Detection and Diagnosis (FDD) and condition monitoring systems are instrumental to improving reliability in the context of manufacturing or operation of systems. The benefits of FDD systems for preventative unscheduled maintenance, for end-of-line production testing, and for potential advanced control to compensate for component degradations are huge. FDD strategies can be model-based or signal-based. Model-based strategies are very effective but are used for systems that can be mathematically modeled. For complex systems for which a meaningful mathematical model is either not available or cannot be derived, signal-based strategies have to be used. This proposal considers the combined application of signal-based and model-based strategies for the condition monitoring and FDD of actuation systems. Condition monitoring will feed into and provide information for the adaptive modification of an advanced feedforward robust control strategy for better performance and for degradation compensation. An Electro-Hydrostatic Actuation (EHA) system used in aerospace will be considered as the application domain in this research. Model-based condition monitoring use estimation strategies. The model-based strategy considered in this proposal will be based on the Smooth Variable Structure Filter (SVSF). The SVSF is a robust filter with features that are uniquely suitable for condition monitoring; it can better accommodate uncertainties due to fault conditions in the system that is being monitored both in terms of its performance and its stability. In general, real-world systems behave according to a number of different operating regimes (or modes). Operating modes can also imply fault conditions. A strategy that can track mode changes in dynamic systems is the Interacting Multiple Model (IMM) concept. As part of its implementation, the IMM requires an estimation strategy. In this research, a new derivation of the SVSF will be combined with IMM to track changes due to fault conditions as part of an enhanced condition monitoring and robust control strategy. For fault conditions that cannot be easily modeled and exhibit a periodic nature, a signal-based strategy will be used. The results from condition monitoring would feed into a robust sliding mode controller that would adapt its feedforward term according to the mode of the actuation system as determined by the above mentioned SVSF/IMM method. Robust refinement of the control input combined with condition monitoring are transformative to the actuation industry.