基于数据与机理模型的复杂工业系统故障诊断与协调容错控制

Under the control and management of distributed control systems (DCS), there are a lot of process data and data that reflect product quality for general complex industrial processes. The proposed project will study data driven and model based fault diagniosis and collaborative fault tolerant control for complex industrial processes that are composed of multiple production units so as to establish a set of fault diagnosis and fault tolerant control algorithms for complex industrial processes. Since once the production structure of complex industrial processes are fixed the set points to the lower layer loop control would determine the product quality, production efficiency and energy and cost savings, these set points would therefore affect the operational state of the processes. As a result, the proposed project will investigate how the set points to control loops can be adjusted in a fault tolerant way using collaborative fault tolerant control. strategies which are based upon data driven and model based fault diagnosis. It is expected that some novel results can be established for data driven and model based fault diagnosis and collaborative fault tolerant control for complex industrial processes in terms of methodologies and techniques. Application studies will be carried out for paper making processes, which would form some foundamental theory and application benchmark on data driven and model based fault diagnosis and collaborative fault tolerant control for complex industrial processes.

复杂工业过程在分布式控制系统（DCS）的控制与管理下有着大量的过程数据和关于产品质量的数据。本课题将研究由多单元组成的复杂工业过程基于数据和机理模型的故障诊断与协调容错控制，建立一套面向复杂工业过程故障诊断和容错控制的基于数据和机理模型相结合的故障诊断。由于复杂工业过程当其生产工艺确定后，底层控制回路设定值是影响产品质量，生产效率和实现节能降耗的主要决策变量，这些回路的设定值也就影响着整个系统的运行状态。因此，本课题拟研究基于数据和机理相结合的过程与能量流综合模型的故障诊断，并在此基础上建立以协调容错控制为手段来调整各生产单元相关联的控制回路的设定值的容错策略。从而形成基于数据和机理模型相结合的复杂工业过程故障诊断与协调容错控制的新方法与关键技术，并在造纸过程等中进行实验验证。为解决复杂工业过程基于数据和机理的故障诊断与容错控制、提供基础理论和应用范例。

复杂工业过程在分布式控制系统（DCS）的控制与管理下有着大量的过程数据和关于产品质量的数据。本课题将研究由多单元组成的复杂工业过程基于数据和机理模型的故障诊断与协调容错控制，建立一套面向复杂工业过程故障诊断和容错控制的基于数据和机理模型相结合的故障诊断。由于复杂工业过程当其生产工艺确定后，底层控制回路设定值是影响产品质量，生产效率和实现节能降耗的主要决策变量，这些回路的设定值也就影响着整个系统的运行状态。因此，本课题拟研究基于数据和机理相结合的过程与能量流综合模型的故障诊断，并在此基础上建立以协调容错控制为手段来调整各生产单元相关联的控制回路的设定值的容错策略。从而形成基于数据和机理模型相结合的复杂工业过程故障诊断与协调容错控制的新方法与关键技术，并在造纸过程等中进行实验验证。为解决复杂工业过程基于数据和机理的故障诊断与容错控制、提供基础理论和应用范例。