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Tuning Guidelines for Model-Predictive Control
Industrial & Engineering Chemistry Research ( IF 3.8 ) Pub Date : 2020-02-18 , DOI: 10.1021/acs.iecr.9b05931
Mohammed Alhajeri 1 , Masoud Soroush 1
Affiliation  

This paper reviews available tuning guidelines for model-predictive control (MPC) from theoretical and practical perspectives. Its primary focus is on the guidelines introduced since the publication of our previous review of MPC tuning guidelines in this same journal in 2010. Since then, new guidelines based on approaches such as pole placement and multiobjective optimization have been proposed, and more autotuning methods have been introduced. This review covers different implementations of MPC such as dynamic matrix control, generalized predictive control, and state-space-model predictive control that requires Kalman filter tuning. The closed-loop performances of a distillation column and the Shell fractionator under model-predictive controllers tuned using four different tuning guidelines are compared through numerical simulations.

中文翻译:

模型预测控制的调整准则

本文从理论和实践的角度回顾了模型预测控制(MPC)可用的调整准则。它的主要重点是自2010年我们在同一期刊上发表MPC调整准则的先前综述以来引入的准则。自那时以来,已经提出了基于极点放置和多目标优化等方法的新准则,并且已经有了更多的自动调整方法被介绍。这篇综述涵盖了MPC的不同实现,例如动态矩阵控制,广义预测控制以及需要卡尔曼滤波器调整的状态空间模型预测控制。通过数值模拟比较了在使用四种不同的调节准则进行调节的模型预测控制器下,蒸馏塔和壳牌分馏塔的闭环性能。
更新日期:2020-02-19
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