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首页> 外文期刊>Advanced Science Letters >Online Dynamic Optimization Strategy for Handling Disturbance in Semi Batch Autocatalytic Esterification Process: Application of Hybrid Optimizer and Simple Re-optimization Activator
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Online Dynamic Optimization Strategy for Handling Disturbance in Semi Batch Autocatalytic Esterification Process: Application of Hybrid Optimizer and Simple Re-optimization Activator

机译：半批量自催化酯化过程中处理干扰的在线动态优化策略：混合优化器的应用及简易重新优化激活

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摘要

The online dynamic-cascaded based optimization is an effective way to handle the effect of uncertainty and disturbance in batch process. The re-optimization and control problems are solved separately in two layers. This work addresses the implementation of an online dynamic cascaded-conditionalbased optimization for handling disturbance occurred in autocatalytic esterification of Propionic Anhydride with 2-Butanol. The online optimization strategy includes an integration of the dynamic re-optimization mechanism (trigger, i.e., ±5% of conversion and dynamic re-optimizer, i.e.,hybrid strategy in maximizing profit), estimator (Cubature Kalman Filter) and controller (dual mode-adaptive Proportional Integrator Derivative). The re-optimization mechanism is activated conditionally by using trigger. The simulation results show that the proposed strategy offers a significantimprovement in semi batch reactor performance if compared to the offline optimization which the optimal trajectories set point is predetermined. Moreover, the online dynamic optimization of temperature and feed flowrate trajectories obtained are able to keep the conversion within acceptablerange (on-spec). Meanwhile, the offline optimization failed to handle the effect of disturbance which results to the off-spec end conversion that can lead to loss in profit.
机译：在线动态级联的优化是一种处理不确定和干扰在批处理过程中的有效方法。重新优化和控制问题在两层中单独解决。这项工作解决了在具有2-丁醇的丙酸酐的自催化酯化中发生的在线动态级联条件的实施，用于处理丙烯酸酐的自催化酸酐。在线优化策略包括动态重新优化机制的集成（触发，即转换和动态重新优化器的±5％，即最大化利润的混合策略），估算器（Cluature Kalman滤波器）和控制器（双模式 - 适当的比例积分器衍生物）。通过使用触发将重新优化机制有条件地激活。仿真结果表明，如果与预先确定最佳轨迹设定点的离线优化相比，该策略在半批量优化相比，该策略在半批量反应器性能下提供了重要的内容。此外，所获得的温度和进料流量轨迹的在线动态优化能够将转换保持在AcceptableRange（on-Spec）内。同时，离线优化未能处理干扰的影响，这导致了可能导致利润损失的异常终端转换。

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