22 citations · 31 across the 6 of their papers we have counts for
6 papers
Enhance Local Consistency in Federated Learning: A Multi-Step Inertial Momentum Approach
Yixing Liu, Yan Sun, Zhengtao Ding +3
Federated learning (FL), as a collaborative distributed training paradigm with several edge computing devices under the coordination of a centralized server, is plagued by inconsis…
Decentralised and Cooperative Control of Multi-Robot Systems through Distributed Optimisation
Yi Dong, Zhongguo Li, Xingyu Zhao +2
Multi-robot cooperative control has gained extensive research interest due to its wide applications in civil, security, and military domains. This paper proposes a cooperative cont…
Data-Driven Load-Current Sharing Control for Multi-Stack Fuel Cell System with Circulating Current Mitigation
Yiqiao Xu, Xiaoyu Guo, Zhen Dong +2
The global trend toward renewable power generation has drawn great attention to hydrogen Fuel Cells (FCs), which have a wide variety of applications, from utility power stations to…
Optimization-Based Ramping Reserve Allocation of BESS for AGC Enhancement
Yiqiao Xu, Alessandra Parisio, Zhongguo Li +2
The transient behavior of Automatic Generation Control (AGC) systems is a critical aspect of power system operation. Therefore, fully extracting the potential of Battery Energy Sto…
Distributed Consensus of Nonlinear Multi-Agent Systems With Mismatched Uncertainties and Unknown High-Frequency Gains (Extended Version)
Gang Wang, Chaoli Wang, Zhengtao Ding +1
This brief addresses the distributed consensus problem of nonlinear multi-agent systems under a general directed communication topology. Each agent is governed by higher-order dyna…
Fully Distributed Adaptive Controllers for Cooperative Output Regulation of Heterogeneous Linear Multi-agent Systems with Directed Graphs
Zhongkui Li, Michael Z. Q. Chen, Zhengtao Ding
This paper considers the cooperative output regulation problem for linear multi-agent systems with a directed communication graph, heterogeneous linear subsystems, and an exosystem…