Machine learning for systems and control



The goal of this course is to provide the student with a comprehensive overview of the main off-the-shelf machine learning techniques for black-box nonlinear model identification and control, and to give the fundamental tools for practical implementation of these techniques. By taking this course, the student masters the main machine learning based modelling and control techniques for nonlinear systems, namely kernel methods, Gaussian process regression, neural networks and control policy learning methods and develops the required skills to implement them for online learning purposes.
Cursusperiode1/09/19 → …