This paper investigates a new consensus-oriented distributed approach for the event-
triggered (ET) economic dispatch problem (EDP) over a smart grid under ramp-rate limits …

Precise representation to undirected weighted network (UWN) is the foundation of
understanding connection patterns inside a massive node set. It can be addressed via a …

We present a framework and algorithms to learn controlled dynamics models using neural
stochastic differential equations (SDEs)--SDEs whose drift and diffusion terms are both …

We propose two parametric approaches to evaluate swing contracts with firm constraints.
Our objective is to define approximations for the optimal control, which represents the …

The originality of this work is introducing a novel Improved Harbor Seal Whiskers Algorithm
(IHSWA) as an innovative and improved optimizer for solving complex hybrid dynamic …

Overparameterized stochastic differential equation (SDE) models have achieved remarkable
success in various complex environments, such as PDE-constrained optimization, stochastic …

This paper presents an artificial neural network (ANN) approach for the development of
position/speed sensorless switched reluctance motor (SRM) drive. A precise estimation of …

We introduce the framework of continuous-depth graph neural networks (GNNs). Neural
graph differential equations (Neural GDEs) are formalized as the counterpart to GNNs where …

How can we transform artificial intelligence (AI) capabilities into engineering systems? That
is, how can we engineer AI systems within budget constraints, certify them with respect to …

Motivated by recent developments in Hamiltonian variational principles, Hamiltonian
variational integrators, and their applications such as to optimization and control, we present …