Research Initiation Award: "On-Line Optimization of Batch Reactors: Experimental Implementation to Polymerization Reactors"

各种各样的特种化学品都是在间歇式反应器中生产的。由于间歇反应器本质上是暂态的，因此主要目标是在间歇周期结束时优化性能指标（如产率）。间歇式反应器运行中的一个主要问题是初始条件和环境条件的变化可能导致批次之间的显著变化，从而导致资源和时间的重大损失。因此，有必要开发可在线实施的优化策略。在这项研究中，将开发一个具有多个输入的批量过程在线优化的方法框架。重点介绍了最优状态反馈律在工业上重要的间歇聚合反应器中的实验实现。以异-双-异-丁腈（AIBN）在甲苯中的苯乙烯与丙烯酸甲酯共聚为模型实验系统，验证了在线优化策略的应用。在第一阶段的研究中，将建立实验系统的数学模型。在第二阶段，将发展多输入间歇反应器终点优化的最优状态反馈律。最优状态反馈在优化性能指标方面的有效性将通过计算机仿真在数学模型上进行验证。在第三阶段，在线优化策略将进行实验实施。几个批量和半批量实验将进行，以证明最优状态反馈的能力，在线计算，当有初始条件的批量变化和过程干扰时的最优操作策略。

Abstract - Palanki - 9409577 A large variety of specialty chemicals are produced in batch reactors. Since batch reactors are transient in nature, the major objective is to optimize a performance index (such as yield) at the end of the batch cycle. A major problem in batch reactor operation is that changes in initial conditions and environmental conditions can cause significant batch-to-batch variations leading to significant losses in resources and time. For this reason, it is necessary to develop optimization strategies that can be implemented on-line. In this study a methodological framework for on-line optimization of batch processes with multiple inputs will be developed. The emphasis is on the experimental implementation of optimal state feedback laws in industrially important batch polymerization reactors. The copolymerization of styrene with methyl acrylate in toluene using aso-bis-iso-butyronitrile (AIBN) has been selected as a model experimental system to demonstrate the application of the on-line optimization strategy. In Phase I of the research, a mathematical model of the experimental system will be developed. In Phase II, optimal state feedback laws will be developed for end-point optimization of batch reactors with multiple inputs. The efficacy of the optimal state feedback in optimizing the performance index will be tested on the mathematical model by computer simulations. In Phase III, the on-line optimization strategy will be implemented experimentally. Several batch and semi-batch experiments will be conducted to demonstrate the ability of the optimal state feedback to calculate, on-line, the optimal operating policy when there are batch to batch variations in initial conditions and process disturbances.