Discrete-time control for variable speed wind turbine

Abstract

This paper proposes a new design approach of discrete sliding mode control for variable speed wind turbine in presence of saturation constraint. The saturation is reported on inputs vector. The design of the sliding surface is formulated as a pole assignment of linear saturated systems in a specific region through convex optimization. It is well know that the mechanisms are investigated in term of the most proposed assumptions to deal with the damping, shaft stiffness and inertia effect of the gear. The existing control techniques do not take into account the dynamical aspect of the wind and the turbine, which leads to significant power losses, besides, they are not robust. Finally, the validity and the applicability of this approach are illustrated by a numerical simulation.

Molecular Energies Derived from Deep Learning: Application to the Prediction of Formation Enthalpies Up to High Energy Compounds

“…The molecules are handled using RDKit [23] and the deep neural networks are used as implemented in the TorchANI library [24] freely available from GitHub. [25] The resulting ANI-1ccx//ANI-1x energies and frequencies are converted to formation enthalpies using Python-ASE. [26] The required parameters, i. e. atom equivalents h s and frequency scaling factor λ, are fitted against the data set of 45 thoroughly vetted experimental values for molecules containing up to 12 heavy atoms introduced by PK.…”