Data-Driven Distributed H ∞ Current Sharing Consensus Optimal Control of DC Microgrids via Reinforcement Learning
Author:
Affiliation:
1. School of Information Science and Engineering, Northeastern University, Shenyang, Liaoning, China
2. Institute of Advanced Technology for Carbon Neutrality, Nanjing University of Posts and Telecommunications, Nanjing, China
Funder
National Key Research and Development Program of China
National Natural Science Foundation of China
Liaoning Revitalization Talents Program
Nature Science Foundation of Liaoning Province of China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx7/8919/10541300/10444694.pdf?arnumber=10444694
Reference38 articles.
1. Supervisory Control of an Adaptive-Droop Regulated DC Microgrid With Battery Management Capability
2. Distributed Power Management for Networked AC–DC Microgrids With Unbalanced Microgrids
3. On the stability of distributed secondary control for DC microgrids with grid-forming and grid-feeding converters
4. Modeling and Control of Islanded DC Microgrid Clusters With Hierarchical Event-Triggered Consensus Algorithm
5. Stable current sharing and voltage balancing in DC microgrids: A consensus-based secondary control layer
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1. Observer-based reinforcement learning for optimal fault-tolerant consensus control of nonlinear multi-agent systems via a dynamic event-triggered mechanism;Information Sciences;2025-01
2. RL-Based Adaptive Optimal Bipartite Consensus Control for Nonlinear Heterogeneous MASs via Event-Triggered State Feedback;IEEE Transactions on Circuits and Systems I: Regular Papers;2024-09
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