With the in-depth advancement of energy saving, emission reduction and manufacturing transformation and upgrading goals, in many engineering fields closely related to thermal physical processes, the dynamic control problems of thermal physical fields to be studied are being derived. The research on distributed output control of thermal physical systems has important scientific significance and broad application prospects. This project puts forward the research topic of spatial distribution output predictive control of the thermal physical system based on the practical demand in the field of engineering technology. Several major scientific issues will also be solved in order to carry out the research on this subject. In this project, the structure parameter governing equation with non-parametric prediction model is constructed based on the distribution parameter mechanism model of thermal physical system. Moreover, spatial reduction mechanism of output distribution prediction model based on model dynamics feature clustering is proposed. The adaptive prediction model of output distribution is also established. This project proposes a reconstruction mechanism based on the system equivalent input inversion, and the online reconstruction problem of thermal physical system’s output space is studied. The unmeasurable output of the system is reconstructed according to the measurement information and prediction results of the system measurement space, which provides support for the feedback correction of the distribution output predictive control process. In the project, a constrained optimization scheme based on the objective functional adaptive idea is proposed. The constrained optimization problem is approximately equivalent to the unconstrained optimization problem in the sense of adaptive objective functional. It provides a feasible way to significantly reduce the calculation cost of distribution output predictive control’s rolling optimization. Through the above-mentioned research on key scientific issues, the spatial distribution output predictive control scheme and its realization method for the complex thermal physical system are established. In addition, through the online coordination of finite control inputs, it is ensured that the thermal physical system can meet the required output distribution. These studies provide scientific support for the related technical fields.
随着节能减排和制造业转型升级目标的深入推进,在许多与热物理过程密切相关的工程领域,正在派生出有待研究的热物理场动态控制问题。研究热物理系统分布输出控制问题,具有重要的科学意义和广阔的应用前景。本项目基于工程技术领域的切实需求,提出热物理系统空间分布输出预测控制研究课题,以及研究该课题需要解决的几个主要科学问题。以热物理系统分布参数机理模型为基础,构造非参数化预测模型结构参数控制方程,提出基于模型动力学特征聚类的输出分布预测模型空间约简机制,建立输出分布自适应预测模型;提出一种基于系统等效输入反演的重构机制,研究热物理系统输出空间的在线重构问题,根据系统测量空间的测量信息及其预测结果,重构系统的不可测输出,为分布输出预测控制过程的反馈校正提供支撑;提出一种基于目标泛函自适应思想的约束优化方案,将约束优化问题近似等效为某种自适应目标泛函意义下的无约束优化问题,为显著降低分布输出预测控制滚动优化计算成本提供可行途径。通过上述关键性科学问题研究,建立复杂热物理系统空间分布输出预测控制方案和实现方法,通过有限控制输入的在线协调,保证热物理系统具有满足要求的输出分布,为相关技术领域提供科学支持。
对关键热物理场进行在线重构和实时控制,是具有重要现实需求的基础性工作。本项目重点研究热传递体系瞬态温度场预测控制面临的几个关键科学问题。.①基于热传递体系分布参数机理模型,建立了温度场非参数化预测模型;根据多模型自适应理论,建立了非线性热传递体系温度场自适应预测模型,并研究了移动热源传热、流体相变传热等非线性系统温度场的自适应预测问题,为温度场预测控制提供必要支持。.②提出一种基于热传递体系映射特征向量模糊聚类的预测模型空间约简机制,确定映射关系具有明显差异的特征空间点,并以特征空间点温度响应预测模型空间有效覆盖整个温度场预测模型空间,显著降低了热传递体系瞬态温度场控制问题的复杂程度。.③研究了基于传热反问题的温度场实时重构问题。依据所提出的分散模糊推理反演和多模型自适应反演方法,反演热传递体系未知热边界条件并在线重构其瞬态温度场,结合现场实验证实了温度场重构结果的可靠性,同时证明了上述重构方案对于非线性热传递体系的自适应能力。.④提出了一种基于映射特征模糊聚类的传热系统瞬态温度场直接重构方法。通过热传递体系内部若干特征空间点温度响应预测模型,有效覆盖整个温度场映射关系,并根据映射特征的模糊隶属关系,利用特征空间点温度响应直接重构瞬态温度场。.⑤建立了热传递体系特征空间点和测量点温度响应之间的时空关联模型,实现代表点温度的实时重构和在线反馈校正。以此为基础,提出了一种基于响应时空关联的温度场预测控制方案,并研究了材料成型过程温度场预测控制等问题。.⑥以流体相变传热系统温度分布自适应预测模型为基础,针对DSG光热发电集热系统过热汽温控制问题,提出了一种基于“热-汽比”及其参考轨迹的自适应预测控制策略。.⑦针对输入约束MlMO系统,建立了一种分散模糊推理预测控制方法,通过控制量模糊集自适应变论域机制,实现模糊推理结果与约束条件的自动匹配。.上述相关研究,为热物理系统分布输出控制奠定了科学基础。
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数据更新时间:2023-05-31
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