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The Multiple Models Predictive Control of Component Content for the Rare Earth Extraction Procession

机译:多模型对稀土提取处理的组分含量的预测控制

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Due to the characteristic of rare earth extraction separation, combined with the material balance model, an approach based on multiple model is presented in this paper. Firstly, by using the data selected in an industrial process, the steady points are obtained, which use the improved subtractive clustering algorithm. The recursive least-square identification method is then adopted to identify-the model parameters. The product Y can be predicted on-line with high purity in the rare earth extraction separation process, which choosing the best performance index function. And an experiment with real industrial operations data is implemented to verify the proposed method. Finally, general predictive controller corresponded is designed for each sub-model so that component content is controlled real-timely and accurately. Simulation results show the effective performance of the referred method.
机译:由于稀土提取分离的特点,结合材料平衡模型,本文提出了一种基于多种模型的方法。首先,通过使用在工业过程中选择的数据,获得稳定点,其使用改进的减数聚类算法。然后采用递归最小二乘识别方法来识别模型参数。可以在稀土提取分离过程中高纯度在线预测产品Y,其选择最佳性能指标功能。并且实施了实际工业运营数据的实验以验证所提出的方法。最后,一般预测控制器对应于每个子模型设计,使得组件内容是实时准确地控制的。仿真结果显示了参考方法的有效性能。

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