Shao Guodong, Jones Albert, Denno Peter, Lu Yan
Systems Integration Division, National Institute of Standards and Technology, Gaithersburg, Maryland 20899 USA.
Proc ASME Int Conf Manuf Sci Eng. 2016;2. doi: 10.1115/MSEC2016-8635.
This paper proposes an approach to integrating advanced process control solutions with optimization (APC-O) solutions, within any factory, to enable more efficient production processes. Currently, vendors who provide the software applications that implement control solutions are isolated and relatively independent. Each such solution is designed to implement a specific task such as control, simulation, and optimization - and only that task. It is not uncommon for vendors to use different mathematical formalisms and modeling tools that produce different data representations and formats. Moreover, instead of being modeled uniformly only once, the same knowledge is often modeled multiple times - each time using a different, specialized abstraction. As a result, it is extremely difficult to integrate optimization with advanced process control. We believe that a recent standard, International Organization for Standardization (ISO) 15746, describes a data model that can facilitate that integration. In this paper, we demonstrate a novel method of integrating advanced process control using ISO 15746 with numerical optimization. The demonstration is based on a chemical-process-optimization problem, which resides at level 2 of the International Society of Automation (ISA) 95 architecture. The inputs to that optimization problem, which are captured in the ISO 15746 data model, come in two forms: goals from level 3 and feedback from level 1. We map these inputs, using this data model, to a population of a meta-model of the optimization problem for a chemical process. Serialization of the metamodel population provides input to a numerical optimization code of the optimization problem. The results of this integrated process, which is automated, provide the solution to the originally selected, level 2 optimization problem.
本文提出了一种在任何工厂内将先进过程控制解决方案与优化（APC - O）解决方案集成的方法，以实现更高效的生产过程。目前，提供实施控制解决方案的软件应用程序的供应商是孤立且相对独立的。每个这样的解决方案都旨在执行特定任务，如控制、模拟和优化——且仅执行该任务。供应商使用不同的数学形式和建模工具来产生不同的数据表示和格式是很常见的。此外，相同的知识往往不是只统一建模一次，而是经常多次建模——每次使用不同的、专门的抽象。因此，将优化与先进过程控制集成极其困难。我们认为，最近的一项标准，即国际标准化组织（ISO）15746，描述了一种能够促进这种集成的数据模型。在本文中，我们展示了一种使用ISO 15746将先进过程控制与数值优化集成的新方法。该演示基于一个化学过程优化问题，该问题位于国际自动化协会（ISA）95架构的第2层。该优化问题的输入以ISO 15746数据模型捕获，有两种形式：来自第3层的目标和来自第1层的反馈。我们使用此数据模型将这些输入映射到化学过程优化问题元模型的一个种群。元模型种群的序列化提供了优化问题数值优化代码的输入。这个自动化集成过程的结果为最初选择的第2层优化问题提供了解决方案。
