Predictive control of a gas-liquid separation plant based on a Gaussian process model

@article{Likar2007PredictiveCO,
  title={Predictive control of a gas-liquid separation plant based on a Gaussian process model},
  author={Bojan Likar and Ju{\vs} Kocijan},
  journal={Computers & Chemical Engineering},
  year={2007},
  volume={31},
  pages={142-152}
}
Gaussian process models provide a probabilistic non-parametric modelling approach for black-box identification of nonlinear dynamic systems. The Gaussian processes can highlight areas of the input space where prediction quality is poor, due to the lack of data or to its complexity, by indicating the higher variance around the predicted mean. Gaussian process models contain noticeably less coefficients to be optimised. This paper demonstrates feasibility of application and realisation of a… CONTINUE READING
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References

Publications referenced by this paper.
Showing 1-10 of 25 references

A case based comparison of identification with neural network and Gaussian process models, Preprints of IFAC ICONS

  • al. Kocijan et, J. 2003b Kocijan, +4 authors C. E. Rasmussen
  • 2003

Dynamic Systems Identification with Gaussian Processes

  • al. Kocijan et, J. 2003a Kocijan, A. Girard, B. Banko, R. Murray-Smith
  • Mathematical and Computer Modelling of Dynamical…
  • 2003

Internal model control based on a Gaussian process prior model

  • R. Murray-Smith, R. Shorten, G. Gregorčič, G. Lightbody
  • 2003

Internal model control based on a Gaussian process prior model, Proceedings of ACC’2003

  • Gregorčič, Lightbody, G 2003Gregorčič, G Lightbody
  • 2003

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