多级串联系统的网络预测控制与目标优化研究

项目名称： 多级串联系统的网络预测控制与目标优化研究

项目编号： No.61203110

项目类型： 青年科学基金项目

立项/批准年度： 2013

项目学科： 自动化学科

项目作者： 张艳

作者单位： 上海海事大学

项目金额： 23万元

中文摘要： 本项目从工业生产过程优化控制的实际出发，将一类复杂大工业过程抽象成多级串联系统的控制与目标优化问题。用分布式控制构造系统的结构框架，建立以控制、约束、目标等为要素的多级串联系统优化控制全局模型；给出系统的整体性能评价体系，利用预测控制长时段预报和滚动优化的思想，充分考虑子系统之间的信息交换和智能协调，研究自适应和非线性网络预测控制算法；研究系统的整体优化目标(例如工业生产过程的最终产品质量)与各子目标(例如各局部子系统的控制量)之间的内在关系，在系统存在各种干扰和不确定因素下，给出多级串联系统的多目标优化算法。结合典型的工业生产过程，研究多级串联系统的网络预测控制与目标优化问题，从而为工业生产中以提高产品质量，降低生产成本为目标的工业生产过程的动态优化控制提供有效的理论方法。

中文关键词： 多级串联系统；预测控制；目标优化；网络控制系统；运动控制

英文摘要： The control and objective optimization problems for serially connected systems (known as the cascade systems in some references) are abstracted from optimization and control problems exist commonly in a class of large-scale industrial processes in this program. Global model with the elements of control variables, constraints and objective functions is built for cascade systems by adopting distributed control structure. Adaptive and nonlinear networked model predictive control algorithms are studied by presenting performance assessment for the whole system, by taking advantage of the long-term prediction and dynamic optimization in model predictive control method, and by considering adequately information exchange and intelligent coordination in subsystems. The inner relationship between the whole optimization objective (the final production quality of industrial processes) and the sub-objectives (control variables of the local subsystems) is studied, and multi-objective optimization algorithms are proposed with the conditions of a large number of disturbances and uncertainty sources exist in the cascade systems. Networked model predictive control and objective optimization algorithms are verified by combining with typical industrial processes, which can improve the production quality, reduce the production cost,

英文关键词： cascade systems；predictive control；objective optimization；networked control systems；motion control