This paper proposes a novel economic Model Predictive Control algorithm aiming at achieving optimal steady-state performance despite the presence of plant-model mismatch or unmeasured nonzero mean disturbances. According to the offset-free formulation, the system’s state is augmented with disturbances and transformed into a new coordinate framework. Based on the new variables, the proposed controller integrates a moving horizon estimator to determine a solution of the nominal system surrounded by a set of potential states compatible with past input and output measurements. The worst cost within a single homothetic tube around the nominal solution is chosen as the economic objective function which is minimized to provide a tightened upper bound for the accumulated real cost within the prediction horizon window. Thanks to the combined use of the nominal system and homothetic tube, the designed optimization problem is recursively feasible and less conservative economic performance bounds are achieved. The proposed controller is demonstrated on a two-tanks system.

本文提出了一种新颖的经济模型预测控制算法，该算法旨在实现最佳的稳态性能，尽管存在工厂模型失配或未测得的非零均值干扰。根据无偏移公式，系统状态会因干扰而增加，并转换为新的坐标框架。基于新的变量，所提出的控制器集成了一个移动的水平估计器，以确定标称系统的解决方案，该解决方案被与过去的输入和输出测量值兼容的一组潜在状态所包围。选择围绕目标解决方案的单个同质管中的最差成本作为经济目标函数，将其最小化以提供预测范围窗口内累积的实际成本的严格上限。由于标称系统和合成管的组合使用，设计的优化问题是递归可行的，并且实现了较保守的经济绩效范围。拟议的控制器在两缸系统上进行了演示。