Dynamic optimization of conditional models with application to chemical process operation and design

条件模型可以定义为系统方程取决于模型解所在位置的模型。 在动态设置中，系统可以以不同的模式运行，模式之间的转换由离散事件触发。 表现出这种类型的行为的化学过程系统的示例是常见的，并且包括可能溢出或干涸的容器、多相系统中的相的出现或消失以及致动器饱和。 不连续行为也可以由控制系统（诸如基于逻辑的监督控制器）引起。 本研究建议解决条件动态模型的优化，主要集中在控制系统引起的模型不连续性的情况下。 要考虑的应用程序包括监管和监督控制系统的设计，在过渡系统的优化，以及动态可操作的工厂的优化设计。 本研究的广泛目标是为这些问题制定有效的配方和解决方案策略，表征特定问题类的收敛特性，并开发与工业相关的新应用。 条件模型的动态优化只是最近才受到过程系统界的关注。 希望通过这项研究，可靠和有效的技术将被开发用于解决这些问题，在新的设计和控制应用的工业意义。

Conditional models may be defined as those in which the system equations depend on where the model solution lies.  In a dynamic setting, the system could operate in different modes, with the transition between modes triggered by discrete events.  Examples of chemical process systems that exhibit behavior of this type are commonplace, and include vessels that could overflow or run dry, appearance or disappearance of a phase in a multiphase system, and actuator saturation.  Discontinuous behavior may also be induced by control systems such as logic-based supervisory controllers.  This research proposal addresses the optimization of conditional dynamic models, focusing primarily on situations in which the model discontinuities are induced by control systems.  Applications to be considered include regulatory and supervisory control system design, optimization of systems in transition, and optimal design of dynamically operable plants.  The broad goals of this research are to develop effective formulation and solution strategies for such problems, characterize the convergence properties for specific problem classes, and develop novel applications of industrial relevance.  Dynamic optimization of conditional models has only recently received attention within the process systems community.  It is hoped that through this research, reliable and efficient techniques will be developed for the solution of such problems in novel design and control applications of industrial significance.