3 papers
eess.SY2026
Actor-Identifier-Critic Reinforcement Learning for Adaptive Model-Free Optimal Control of Nonlinear Systems with Stochastic Packet Dropouts
Kianoush Aqabakee, Kosar Behnia, Amirhossein Heydarian Ardakani +2
Packet dropouts in control systems poses a critical challenge, as it can significantly compromise system performance and stability. In these conditions, classical controllers often…
eess.SY2025
Data driven approach towards more efficient Newton-Raphson power flow calculation for distribution grids
Shengyuan Yan, Farzad Vazinram, Zeynab Kaseb +8
Power flow (PF) calculations are fundamental to power system analysis to ensure stable and reliable grid operation. The Newton-Raphson (NR) method is commonly used for PF analysis…
eess.SY2023
Autonomous Driving using Residual Sensor Fusion and Deep Reinforcement Learning
Amin Jalal Aghdasian, Amirhossein Heydarian Ardakani, Kianoush Aqabakee +1
This paper proposes a novel approach by integrating sensor fusion with deep reinforcement learning, specifically the Soft Actor-Critic (SAC) algorithm, to develop an optimal contro…