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Robust and Asymmetric Assessment of the Benefits from Improved Control – Industrial Validation

机译:从改进控制 - 工业验证的鲁棒和不对称评估益处

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Quality of the control system significantly contributes to the overall process technological and financial results. Plant throughput, environmental footprint and energy consumption push plants towards their technological limitations requiring better operation closer to constraints. Any improvement initiative should be predated with the estimation of the potential benefits associated with the rehabilitation project. The same applies to the control improvements. The assessment is always based on the performance indicators. Classical the same limit method is based on the Gaussian approach. However, investigation of industrial data frequently is not compliant with normal assumption about the properties of the variables. This paper extends the Gaussian approach with the use of robust (Huber) statistics and asymmetric Pearson type IV probability density function.
机译:控制系统的质量显着促进整体过程技术和财务结果。植物吞吐量,环境足迹和能源消耗推动工厂的技术限制,需要更好地靠近约束的操作。应通过估计与康复项目相关的潜在福利来估计任何改进倡议。这同样适用于控制改进。评估始终基于绩效指标。古典相同的极限方法是基于高斯方法。然而,经常对工业数据的调查不符合关于变量性质的正常假设。本文扩展了使用鲁棒(Huber)统计和非对称Pearson型概率密度函数的高斯方法。

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