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Soft sensor design for variable time delay and variable sampling time
Journal of Process Control ( IF 4.2 ) Pub Date : 2020-08-01 , DOI: 10.1016/j.jprocont.2020.07.001
Fritjof Griesing-Scheiwe , Yuri A.W. Shardt , Gustavo Pérez-Zuñiga , Xu Yang

Abstract Often industrial variables can be difficult to measure due to such factors as extreme conditions or complex compositions. In such cases, soft sensors have been developed that use available system information and measurements to estimate these difficult-to-obtain variables. In practice, the measurements that are to be estimated by a soft sensor are often infrequently measured or delayed. Occasionally, these sampling times or delays are time varying. At present, most research has considered these parameters to be time invariant, and thus, there is a need to consider the time-varying case. Therefore, this paper will evaluate the impact of time-varying delays and sampling times for the design of a data-driven soft sensor. Modifications will be proposed that will increase the robustness and performance of the soft sensor. The reliability of the estimate will be shown using the Bauer–Premaratne–Duran Theorem. Furthermore, the proposed soft sensor system will be tested using simulations of a continuous stirred tank reactor (CSTR) and an reverse osmosis plant. Simulation showed that the modified soft sensor gives good estimates, whereas the traditional soft sensor gives an unstable estimate for the CSTR and reverse osmosis plant.

中文翻译:

可变延时和可变采样时间的软传感器设计

摘要 由于极端条件或复杂成分等因素,工业变量通常难以测量。在这种情况下,已经开发出软传感器,使用可用的系统信息和测量来估计这些难以获得的变量。实际上,由软传感器估计的测量值通常很少测量或延迟。有时,这些采样时间或延迟是随时间变化的。目前,大多数研究都认为这些参数是时不变的,因此需要考虑时变情况。因此,本文将评估时变延迟和采样时间对数据驱动软传感器设计的影响。将提出修改,以提高软传感器的鲁棒性和性能。估计的可靠性将使用 Bauer-Premaratne-Duran 定理来显示。此外,将使用连续搅拌釜反应器 (CSTR) 和反渗透装置的模拟来测试提议的软传感器系统。仿真表明,改进的软传感器给出了很好的估计,而传统的软传感器对 CSTR 和反渗透装置给出了一个不稳定的估计。
更新日期:2020-08-01
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