8 citations · 12 across the 8 of their papers we have counts for
8 papers
GenControl: Generative AI-Driven Autonomous Design of Control Algorithms
Chenggang Cui, Jiaming Liu, Peifeng Hui +2
Designing controllers for complex industrial electronic systems is challenging due to nonlinearities and parameter uncertainties, and traditional methods are often slow and costly.…
Automated Heuristic Design for Unit Commitment Using Large Language Models
Junjin Lv, Chenggang Cui, Shaodi Zhang +3
The Unit Commitment (UC) problem is a classic challenge in the optimal scheduling of power systems. Years of research and practice have shown that formulating reasonable unit commi…
Dynamic Incentive Strategies for Smart EV Charging Stations: An LLM-Driven User Digital Twin Approach
Yichen Sun, Chenggang Cui, Chuanlin Zhang +1
This paper presents an enhanced electric vehicle demand response system based on large language models, aimed at optimizing the application of vehicle-to-grid technology. By levera…
Electric Vehicle User Charging Behavior Analysis Integrating Psychological and Environmental Factors: A Statistical-Driven LLM based Agent Approach
Chuanlin Zhang, Junkang Feng, Chenggang Cui +6
With the growing adoption of electric vehicles (EVs), understanding user charging behavior has become critical for grid stability and transportation planning. This study investigat…
On Physics-Informed Neural Network Control for Power Electronics
Peifeng Hui, Chenggang Cui, Pengfeng Lin +3
Considering the growing necessity for precise modeling of power electronics amidst operational and environmental uncertainties, this paper introduces an innovative methodology that…
Large Language Models based Multi-Agent Framework for Objective Oriented Control Design in Power Electronics
Chenggang Cui, Jiaming Liu, Junkang Feng +3
Power electronics, a critical component in modern power systems, face several challenges in control design, including model uncertainties, and lengthy and costly design cycles. Thi…
Transferring Reinforcement Learning for DC-DC Buck Converter Control via Duty Ratio Mapping: From Simulation to Implementation
Chenggang Cui, Tianxiao Yang, Yuxuan Dai +1
Reinforcement learning (RL) control approach with application into power electronics systems has become an emerging topic whilst the sim-to-real issue remains a challenging problem…
An Intelligent Control Strategy for buck DC-DC Converter via Deep Reinforcement Learning
Chenggang Cui, Nan Yan, Chuanlin Zhang
As a typical switching power supply, the DC-DC converter has been widely applied in DC microgrid. Due to the variation of renewable energy generation, research and design of DC-DC…