Abstract
The paper discusses the development of a soft sensor (SS) for an MTBE plant in the cases when the training sample either is small or does not comprise the whole of quality range because of process plant non-stationarity as well as the difficulty and high cost of retrieving more information. In order to build a soft sensor that provides higher accuracy in estimating the quality of the output product, an algorithm for extending the initial training sample using a rigorous model of the distillation column of the methyl-tert-butyl ether production under condition of exactly unknown values of the Murphree trays efficiency has been proposed. The resulting SS enables 40% improvement of product quality prediction.
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Samotylova, S., Torgashov, A. Developing a Soft Sensor for MTBE Process Based on a Small Sample. Autom Remote Control 81, 2132–2142 (2020). https://doi.org/10.1134/S0005117920110120
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DOI: https://doi.org/10.1134/S0005117920110120