This paper proposes a new analytical tuning strategy for Model Predictive Control (MPC). In the proposed approach, MPC tuning problem is restated as a pole-zero placement problem. New analytically tuning equations are given and a deep study on the places of poles and zeros of the closed-loop system is performed. It is known that, appropriate zero placement can improve the robust stability of the closed-loop system, so the proposed tuning strategy can be applicable. In MPC tuning strategies, analytical equations are very interesting and useful. To achieve analytical equations, First Order plus Dead Time models are used in this work. These models with adequate accuracy can describe many industrial processes. With simulation studies, the effectiveness of the proposed pole-zero assignment strategy is indicated.

中文翻译：

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模型预测控制中的零极点分配，使用分析调整方法

本文提出了一种新的模型预测控制 (MPC) 分析调整策略。在所提出的方法中，MPC 调谐问题被重新表述为零极点放置问题。给出了新的解析调谐方程，并对闭环系统的极点和零点位置进行了深入研究。众所周知，适当的置零可以提高闭环系统的鲁棒稳定性，因此所提出的整定策略是适用的。在 MPC 调整策略中，解析方程非常有趣和有用。为了获得解析方程，在这项工作中使用了一阶加死区时间模型。这些具有足够精度的模型可以描述许多工业过程。通过仿真研究，表明了所提出的零极点分配策略的有效性。