This article addresses the plant‐model mismatch estimation problem for linear multiple‐input and multiple‐output systems operating under the dynamic matrix control (DMC) implementation of model predictive control. An autocovariance‐based method is proposed, aiming to identify parameter values that minimize the discrepancy between the theoretical autocovariance matrices derived from implementing the (explicit) DMC control law and the sampled autocovariance matrices calculated from operating data. We provide proof that the method results in unbiased estimates. A means for dealing with potential overfitting issues caused by the finite step response models used in DMC in practice is proposed. Several examples are presented to illustrated the theoretical developments.

中文翻译：

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动态矩阵控制系统的数据驱动的工厂模型失配估计

本文解决了在模型预测控制的动态矩阵控制（DMC）实现下运行的线性多输入多输出系统的工厂模型失配估计问题。提出了一种基于自协方差的方法，旨在确定参数值，以最小化实现（显式）DMC控制律而得出的理论自协方差矩阵与从运行数据计算得出的采样自协方差矩阵之间的差异。我们提供了证明，该方法可导致无偏估计。提出了一种处理DMC在实践中使用的有限阶跃响应模型引起的潜在过度拟合问题的方法。给出了几个例子来说明理论发展。