collaborators

8 papers

eess.SY2026

From Privileged Control to Deployable Adaptation:Fusing Mechanism-Guided Task Reduction with Learned Behavior

Xitong Niu, Peifeng Hui, Zheyong Jiang +2

Simultaneous input-gain variation and large additive disturbance create a control problem in which a fixed observer or nominal controller may be unable to reproduce the performance…

eess.SY2026

Artificial Intelligence for Power-Converter-Rich Electrical Systems: A Review

Pengfeng Lin, Yuan Gao, Yuxi Tang +8

Power-converter-rich electrical systems, formed by renewable generation, electrified transportation, and inverter-based resources, exhibit strongly nonlinear dynamics, multi-physic…

eess.SY2026

Collaborative Optimization Framework of Battery Charging / Swapping Stations for eVTOLs Based on Closed-Loop Supply Chain and Space-Time Network

Pengfeng Lin, Miao Zhu, Jiahui Sun +4

Electric vertical take-off and landing (eVTOL) aircraft, by virtue of their advantages such as high efficiency, environmental friendliness, and low noise, are regarded as an effect…

eess.SY2026

Model-Free DRL Control for Power Inverters: From Policy Learning to Real-Time Implementation via Knowledge Distillation

Yang Yang, Chenggang Cui, Xitong Niu +2

In response to the trade-off between control performance and computational burden hindering the deployment of Deep Reinforcement Learning (DRL) in power inverters, this paper prese…

cs.AI2026

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…

eess.SY2025

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.…