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Real-time optimization of a novel hydroformylation process by using transient measurements in modifier adaptation

机译:新型加氢甲酰化工艺的实时优化通过使用改进剂适应中的瞬态测量

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This paper deals with the use of transient measurements in the steady-state optimization of a hydroformylation process in the presence of plant-model mismatch. The key idea is to predict steady states from the measurements obtained during the transients of the process. The predicted steady states are then employed in the modifier adaptation with quadratic approximation algorithm to drive the operation of the process to its economic optimum. Simulation results show the promising performance of the proposed scheme.
机译:本文涉及在植物模型不匹配存在下使用瞬态测量在稳态优化的加氢甲酰化过程中。关键思想是从过程的瞬变期间获得的测量值预测稳定状态。然后,使用二次近似算法在修改器适应中采用预测的稳态,以将过程的运行驱动到其经济最优的过程。仿真结果表明了拟议方案的有希望的性能。

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