A batch to batch optimal control strategy based on multiinput multioutput adaptive hinging hyperplanes (MIMO AHH) prediction and Kalman filter correction is proposed for the products quality control of the batch process. The model of AHH is one kind of piecewise linear models and is extended to the MIMO case in this article. The MIMO AHH is then used to develop the predictive model of the batch process. Due to the model‐plant mismatch and unknown disturbances, the optimal control policy calculated based on the MIMO AHH predictive model may not be optimal when applied to the true process. The Kalman filter is then utilized to correct the predictions of the current batch by considering the information of former batches. The effectiveness of the proposed strategy is verified through the simulation of a styrene batch polymerization reactor.

中文翻译：

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基于多输入多输出自适应铰链超平面预测和卡尔曼滤波校正的逐批最优控制

提出了一种基于多输入多输出自适应铰链超平面（MIMO AHH）预测和卡尔曼滤波校正的批量到批量的最优控制策略，用于批量过程的产品质量控制。AHH模型是一种分段线性模型，在本文中扩展为MIMO情况。然后，将MIMO AHH用于开发批处理过程的预测模型。由于模型工厂不匹配和未知干扰，基于MIMO AHH预测模型计算的最优控制策略在应用于真实过程时可能不是最优的。然后，通过考虑先前批次的信息，利用卡尔曼滤波器来校正当前批次的预测。通过对苯乙烯间歇聚合反应器的仿真，验证了所提出策略的有效性。