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A method of MPC model error detection

机译:一种MPC模型错误检测方法

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摘要

This work introduces a method of multivariable model error detection in model prediction control (MPC). The idea is to use non-disturbing small sinusoidal test signals to obtain accurate estimates of process frequency responses at several frequency points. Then, the differences between estimated frequency responses and the frequency responses of current MPC model are used to form the model error index matrix which is used to access the model error of the MPC controller. An upper error bound is developed for quantifying the error of frequency response estimation. The method works in closed-loop operation with the MPC controller online. Simulation studies are used to demonstrate the use of the method.
机译:这项工作介绍了模型预测控制(MPC)中的多变量模型错误检测方法。这个想法是使用无干扰的小正弦测试信号来获得在几个频率点上的过程频率响应的准确估计。然后,将估计的频率响应与当前MPC模型的频率响应之间的差异用于形成模型误差指标矩阵,该矩阵用于访问MPC控制器的模型误差。开发了误差上限,用于量化频率响应估计的误差。该方法在MPC控制器在线的闭环运行中工作。仿真研究用于证明该方法的使用。

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