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

摘要- Palanki - 9409577 在间歇式反应器中生产各种特种化学品。由于间歇式反应器本质上是瞬态的，因此主要目标是在间歇循环结束时优化性能指标（如产率）。 间歇式反应器操作中的主要问题是初始条件和环境条件的变化可引起显著的批次间变化，导致资源和时间的显著损失。 因此，有必要制定可以在线实施的优化策略。 在这项研究中，将开发一个方法框架，在线优化的间歇过程与多个输入。 重点是在工业上重要的间歇聚合反应器的最优状态反馈法的实验实施。 以苯乙烯和丙烯酸甲酯在甲苯中的异二异丁腈（AIBN）共聚合为模型实验系统，验证了在线优化策略的应用。 在研究的第一阶段，将开发实验系统的数学模型。 在第二阶段，最优状态反馈法将开发用于具有多个输入的间歇式反应器的终点优化。 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测试。 在第三阶段，在线优化策略将实验实施。 几个批次和半批次的实验将进行证明的能力，最优状态反馈计算，在线，最优的操作策略时，有批次的初始条件和过程干扰的变化。

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.