Fault Tolerant MPC for Fed-Batch Penicillin Production

Carlos A. Duran-Villalobos, B. Lennox, S. Goldrick
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Abstract

Biopharmaceutical manufacturing is an inherently complex operation with industrial-scale control strategies often failing to accurately account for faults and product variation that can result in significant economic losses. In response, this work presents a fault-tolerant Model Predictive Control (MPC) strategy which solves a modified version of a Quadratic Programming (QP) problem, using a data-driven adaptive Multivariate Partial Least Square (MPLS) model. The proposed technique is applied to an industrial simulation of a fed-batch process and found to improve operations significantly.
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用于联产青霉素生产的容错 MPC
生物制药生产本身就是一项复杂的操作,工业规模的控制策略往往无法准确考虑故障和产品变异,从而导致重大经济损失。为此,本研究提出了一种容错模型预测控制(MPC)策略,利用数据驱动的自适应多变量偏最小二乘法(MPLS)模型,求解修正版的二次编程(QP)问题。所提出的技术被应用于喂料批量流程的工业仿真,发现它能显著改善操作。
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