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  Predictive control with Gaussian process models

Kocijan, J., Murray-Smith, R., Rasmussen, C., & Likar, B. (2003). Predictive control with Gaussian process models. In B. Zajc, & M. Tkalcic (Eds.), IEEE Region 8 EUROCON 2003: Computer as a Tool (pp. 352-356). Piscataway, NJ, USA: IEEE. doi:10.1109/EURCON.2003.1248042.

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 Creators:
Kocijan, J, Author
Murray-Smith, R, Author
Rasmussen, CE1, 2, Author           
Likar, B, Author
Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              

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 Abstract: This paper describes model-based predictive control based on Gaussian processes. Gaussian process models provide a probabilistic non-parametric modelling approach for black-box identification of nonlinear dynamic systems. It offers more insight in variance of obtained model response, as well as fewer parameters to determine than other models. The Gaussian processes can highlight areas of the input space where prediction quality is poor, due to the lack of data or its complexity, by indicating the higher variance around the predicted mean. This property is used in predictive control, where optimisation of control signal takes the variance information into account. The predictive control principle is demonstrated on a simulated example of nonlinear system.

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 Dates: 2003-12
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: 2283
DOI: 10.1109/EURCON.2003.1248042
 Degree: -

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Title: IEEE Region 8 EUROCON 2003: Computer as a Tool
Place of Event: Ljubljana, Slovenia
Start-/End Date: 2003-09-22 - 2003-09-24

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Title: IEEE Region 8 EUROCON 2003: Computer as a Tool
Source Genre: Proceedings
 Creator(s):
Zajc, B, Editor
Tkalcic, M, Editor
Affiliations:
-
Publ. Info: Piscataway, NJ, USA : IEEE
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 352 - 356 Identifier: ISBN: 0-7803-7763-X