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Application of Gaussian Processes to the Modelling and Control in Process Engineering

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Innovations in Intelligent Machines-5

Part of the book series: Studies in Computational Intelligence ((SCI,volume 561))

Abstract

Many engineering systems can be characterized as complex since they have a nonlinear behaviour incorporating a stochastic uncertainty. It has been shown that one of the most appropriate methods for modelling of such systems is based on the application of Gaussian processes (GPs). The GP models provide a probabilistic non-parametric modelling approach for black-box identification of nonlinear stochastic systems. This chapter reviews the methods for modelling and control of complex stochastic systems based on GP models. The GP-based modelling method is applied in a process engineering case study, which represents the dynamic modelling and control of a laboratory gas–liquid separator. The variables to be controlled are the pressure and the liquid level in the separator and the manipulated variables are the apertures of the valves for the gas flow and the liquid flow. GP models with different regressors and different covariance functions are obtained and evaluated. A selected GP model of the gas–liquid separator is further used to design an explicit stochastic model predictive controller to ensure the optimal control of the separator.

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Author information

Authors and Affiliations

  1. Department of Systems and Control, Jožef Stefan Institute, Jamova cesta 39, 1000, Ljubljana, Slovenia

    Juš Kocijan

  2. Centre for Systems and Information Technologies, University of Nova Gorica, Vipavska 13, 5000, Nova Gorica, Slovenia

    Juš Kocijan

  3. Institute of System Engineering and Robotics, Bulgarian Academy of Sciences, Acad. G. Bonchev Street, Bl. 2, P. O. Box 79, 1113, Sofia, Bulgaria

    Alexandra Grancharova

Authors
  1. Juš Kocijan
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  2. Alexandra Grancharova
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Correspondence to Alexandra Grancharova .

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Editors and Affiliations

  1. Department of Automation and Applied Informatics, "Aurel Vlaicu" University of Arad, Arad, Romania

    Valentina Emilia Balas

  2. Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, Sofia, Bulgaria

    Petia Koprinkova-Hristova

  3. Faculty of Education, Science, Technology and Mathematics, University of Canberra, Canberra, Australia

    Lakhmi C. Jain

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Kocijan, J., Grancharova, A. (2014). Application of Gaussian Processes to the Modelling and Control in Process Engineering. In: Balas, V., Koprinkova-Hristova, P., Jain, L. (eds) Innovations in Intelligent Machines-5. Studies in Computational Intelligence, vol 561. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-43370-6_6

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  • DOI: https://doi.org/10.1007/978-3-662-43370-6_6

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