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: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=760186
• 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-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.

产品质量和可靠性仍然是制造商的首要任务之一，尽管需要较低的成本，但必须保持这些优先级。设备供应商确保其生产产品的质量和可靠性的需求正在增加。高级控制与高级条件监测的结合越来越重要，并且正在成为下一代产品的组成部分和基本要素。故障检测和诊断（FDD）和状态监控系统对在制造或系统运行的背景下可靠性提高了可靠性。 FDD系统对预防性外界维护，线结束生产测试以及潜在的高级控制以补偿组件降低的好处是巨大的。 FDD策略可以基于模型或基于信号。基于模型的策略非常有效，但用于可以通过数学建模的系统。对于不可用或无法得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。该建议考虑了基于信号和基于模型的策略在驱动系统的状况监测和FDD中的合并应用。条件监控将进食并提供信息，以自适应修改高级馈电稳健控制策略，以提高性能和退化补偿。航空航天中使用的电静电驱动（EHA）系统将被视为本研究中的应用领域。基于模型的条件监视使用估计策略。本提案中考虑的基于模型的策略将基于平滑可变结构过滤器（SVSF）。 SVSF是一个可靠的滤波器，具有适合条件监控的特征；由于系统中的故障状况，它在其性能和稳定性方面都可以更好地适应不确定性。通常，现实世界系统根据许多不同的操作制度（或模式）行事。操作模式也可能意味着故障条件。可以跟踪动态系统模式变化的策略是相互作用的多个模型（IMM）概念。作为实施的一部分，IMM需要估算策略。在这项研究中，SVSF的新推导将与IMM相结合，以跟踪由于故障条件而导致的变化，这是增强的状况监测和稳健的控制策略的一部分。对于无法轻松建模并表现出周期性的断层条件，将使用基于信号的策略。条件监控的结果将进出一个可靠的滑动模式控制器，该控制器将根据上述SVSF/INM方法确定的致动系统模式调整其前馈期限。对控制输入与条件监测结合的强大完善是对驱动行业的变化。