Model-based optimization of water resource recovery facilities

废水处理行业正在发生一个重要的变化：从一个处理废水的行业转变为一个带来更积极信息的行业：它生产清洁水，并回收废水中含有的肥料和能源。WRRFs旨在提供有价值的产品，这些产品可以部分替代通过其他方式生产的产品（通常在化学工业中），这一事实导致了该设施产出规格的重大变化：不再处理废水和生物固体，而是必须与市场上已有的产品竞争的产品。这些更严格的规范将对保证wrrf产品质量所需的过程控制系统提出挑战。考虑到收集控制系统所依赖的高质量数据的困难（最近使用部分自动化数据验证的实际研究报告数据丢失5%至60%），必须部署重要的研究工作来创建过程监控和控制系统，以始终保持这些严格的产品规格。***在接下来的5年里，这项发现基金的研究计划将开发控制系统，这些系统受益于新算法的能力，不仅可以可靠地检测测量设备中的故障，还可以找出传感器的问题（故障诊断）。有了这些知识，问题当然可以通过适当的维护或更换传感器来处理，但在此之前，控制系统必须能够仍然充分地执行。容错是一种方法学，随后将采用历史信息或简单模型来替代错误数据。如果故障太具有破坏性，则必须采用不依赖于这些数据的不同控制策略。一种基于后撤策略的所谓控制重新配置必须发生。最后，由于对资源回收设施的要求越来越严格，因此将评价一种似乎特别适合这种有多种目标和复杂行为的情况的控制办法：寻求外部控制。它的直觉性质将确保这项研究的结果有一个很好的机会，使其付诸实践，并产生预期的性能进步。***该项目将培养8名研究生（4名博士和4名硕士），至少3名本科生，1名博士后和1名负责行业标准中试工厂的技术人员，该中试工厂将开发和测试不同的方法。这些HQP将通过参与研究项目的不同方面、接触国内和国际研究以及通过行业标准试点设施的工作获得广泛的技能。

An important change is happening to the wastewater industry: a paradigm shift is occurring from an industry that treats wastewater to an industry that brings a more positive message: it produces clean water, and recovers fertilizers and energy contained in used' water. The fact that WRRFs aim at delivering valued products that can partially replace those produced by other means (typically in the chemical industry) leads to a big change in specifications of the outputs of the facility: no longer treated wastewater and biosolids, but products that have to compete with what is already on the market. These tighter specifications will impose a challenge on the process control systems that will be required to guarantee the quality of the products of the WRRFs. Given the difficulties in collecting high quality data on which the control systems rely to act upon the system (recent practical studies using partially automated data validation report data losses of 5 to 60%), important research efforts have to be deployed to create the process monitoring and control systems that maintain these tight product specifications at all time.***Over the next 5 years the research program of this Discovery grant will develop control systems that benefit from the ability of new algorithms to not only reliably detect faults in the measurement equipment but can also find out what is wrong with the sensors (fault diagnosis). With this knowledge the problem can of course be handled through proper maintenance or replacement of the sensor, but until that happens, the control system must be able to still perform adequately. Fault-accommodation is the methodology that is then put in place and methods will be developed to replace the faulty data by using either historical information or simple models. In case the fault is too disruptive, a different control strategy will have to be adopted that does not rely on these data. A so-called control reconfiguration based on a fall-back strategy has to occur. Finally, because the requirements imposed on resource recovery facilities are becoming so much more stringent, a control approach that seems particularly suited for this type of situations with multiple objectives and complex behavior, will be evaluated: Extermum seeking control. Its intuitive nature will make sure that the results of this research have a good chance to make it to practice and generate the anticipated advances in performance.***The project will train 8 graduate students (4 PhD and 4 MSc), at least 3 undergraduates, a postdoctoral fellow and a technician responsible for the industry standard pilot plant on which the different methods will be developed and tested. These HQP will acquire a wide range of skills thanks to the involvement in the different aspects of the research project, the exposure to national and international research and to practice through the work on an industry standard pilot facility.