Developers are increasingly relying on large language models (LLMs) for everyday computing tasks such as fixing bugs, ...

Abstract: This paper proposes a model for hierarchical combination of deep reinforcement learning (DRL) with quadratic programming for distribution system restoration after major outages. In the ...

Abstract: In this article, we investigate the optimal control problem for an unknown linear time-invariant system. To solve this problem, a novel composite policy iteration algorithm based on adaptive ...

Abstract: This paper investigates the transient stability of the grid-forming and grid-following (GFM-GFL) paralleled system based on the Lyapunov direct method. To achieve this goal, an improved ...

Abstract: Learning-based control methods for industrial processes leverage the repetitive nature of the underlying process to learn optimal inputs for the system. While many works focus on linear ...

Learning to program in C on an online platform can provide structured learning and a certification to show along with your resume. Learning C can still be useful in 2026, especially if you want to ...

Abstract: For meshed power networks, even though the conic relaxation is shown to be exact, the relaxation of angles may not be exact using the existing Second-Order Cone Programming (SOCP) based ...

Abstract: This article studies the control problem for safety-critical multiagent systems based on quadratic programming (QP). Each controlled agent is modeled as a cascade connection of an integrator ...

Mikeie Reiland is a staff writer for Education at Forbes Advisor. Before coming to Forbes Advisor, he wrote magazine journalism for publications like the Oxford American, Bitter Southerner, and Gravy.

Abstract: Existing energy storage systems (ESSs) are mostly deployed at locations that generate the maximum economic benefits of active distribution networks (ADNs). However, mobile energy storage ...

Abstract: This paper presents the bias-policy iteration, a modified adaptive dynamic programming method, to achieve optimal control design of discrete-time nonlinear systems. Firstly, the formulation ...