Gaussian Processes for Learning and Control: A Tutorial with Examples

IEEE Control Systems Magazine, pp. 53-86, 2018.

Cited by: 19|Bibtex|Views19|DOI:https://doi.org/10.1109/MCS.2018.2851010
EI WOS
Other Links: academic.microsoft.com

Abstract:

Many challenging real-world control problems require adaptation and learning in the presence of uncertainty. Examples of these challenging domains include aircraft adaptive control under uncertain disturbances [1], [2], multiple-vehicle tracking with space-dependent uncertain dynamics [3], [4], robotic-arm control [5], blimp control [6], ...More

Code:

Data:

Your rating :
0

 

Tags
Comments