Advanced integrated Control and Monitoring of Actuation Systems

驱动系统的先进集成控制和监控

• 批准号: RGPIN-2020-05735
• 负责人: Habibi, Saeid
• 金额: $ 2.84万
• 依托单位: McMaster University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=717934
• 关键词: Advanced; integrated; Control; Monitoring; Actuation

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-ofline 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.

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，以确保他们生产的产品的质量和可靠性正在增加。先进控制与先进状态监测相结合的重要性日益增加，并正在成为下一代产品不可或缺的基本要素。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系统在预防性计划外维护、生产线末端测试以及用于补偿部件退化的潜在先进控制方面的好处是巨大的。FDD策略可以是基于模型的或基于信号的。基于模型的策略非常有效，但用于可以数学建模的系统。对于复杂的系统，一个有意义的数学模型要么是不可用的，要么不能推导出，基于信号的策略必须使用。该建议考虑了基于信号和基于模型的策略的组合应用，用于执行系统的状态监测和故障诊断。状态监测将反馈到先进的前馈鲁棒控制策略的自适应修改中，并提供信息，以获得更好的性能和退化补偿。本研究以航空航天领域的电液作动系统为应用领域。 基于模型的状态监测使用估计策略。本提案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功能;它可以更好地适应由于系统中的故障状态而导致的不确定性，该系统在性能和稳定性方面都受到监测。一般来说，现实世界的系统根据许多不同的操作制度（或模式）来运行。操作模式也可能意味着故障条件。可以跟踪动态系统中的模式变化的策略是交互式多模型（IMM）概念。作为其实现的一部分，IMM需要一个估计策略。在这项研究中，一个新的推导SVSF将与IMM相结合，以跟踪由于故障条件的变化，作为一个增强的状态监测和鲁棒控制策略的一部分。对于无法轻松建模且表现出周期性的故障条件，将使用基于信号的策略。来自状态监测的结果将被馈送到鲁棒滑模控制器中，该鲁棒滑模控制器将根据由上述SVSF/IMM方法确定的致动系统的模式来调整其前馈项。控制输入的鲁棒细化与状态监测相结合，对驱动行业具有变革性意义。