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Gaussian Process-Based Inferential Control System

  • Ali Abusnina
  • Daniel Kudenko
  • Rolf Roth
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 299)

Abstract

Gaussian process are emerging as a relatively new soft sensor building technique with promising results. This paper proposes a Gaussian Process Inferential Control System (GP-ICS) to control infrequently-measured variables in industrial processes. This is achieved by utilising an adaptive Gaussian process-based soft sensor to provide accurate reliable and continuous online predictions of difficult to measure variables and feeding them back to a PI controller. The contributions of the paper are i) the introduction of Gaussian process-based soft sensors in building inferential control systems, ii) we empirically show that the Gaussian process based inferential controller outperforms the ANN-based controller.

Keywords

soft sensors Gaussian processes ANN inferential control 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.University of YorkYorkUK
  2. 2.Evonik Industries AGMarlGermany

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