GP-MRAC

Abstract: GP-MRAC extends BKR-CL to incorporate Bayesian estimation through Gaussian process regression. Like BKR-CL, it is fully data-driven and starts with the zero function (i.e., an empty kernel machine) and builds up the learnt representation with data collected during online operation. Combining machine learning analysis methods with controls-based Lyapunov stability analysis leads to proven stability of the method.

More to be written soon.

The abstract and paper can be found on IEEE Xplore.