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Data-Efficient Autotuning With Bayesian Optimization: An Industrial Control Study.

IEEE Transactions on Control Systems Technology, no. 3 (2020): 730-740

Cited: 0|Views35
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Abstract

Bayesian optimization (BO) is proposed for automatic learning of optimal controller parameters from experimental data. A probabilistic description (a Gaussian process) is used to model the unknown function from controller parameters to a user-defined cost. The probabilistic model is updated with data, which is obtained by testing a set of...More

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Author
Matthias Neumann-Brosig
Matthias Neumann-Brosig
Dieter Schwarzmann
Dieter Schwarzmann
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