activity
20072022
most citedTracking control for multi-agent consensus with an active leader and variable topology

2.1k citations · 4.4k across the 56 of their papers we have counts for

collaborators

57 papers

math.OC2022★ 1 cited

Distributed Prediction-Correction Algorithms for Time-Varying Nash Equilibrium Tracking

Ziqin Chen, Ji Ma, Peng Yi +1

This paper focuses on a time-varying Nash equilibrium trajectory tracking problem, that is applicable to a wide range of non-cooperative game applications arising in dynamic enviro…

eess.SY2022

Small-Gain Theorem for Safety Verification under High-Relative-Degree Constraints

Ziliang Lyu, Xiangru Xu, Yiguang Hong

This paper develops a small-gain technique for the safety analysis and verification of interconnected systems with high-relative-degree safety constraints. In this technique, input…

math.OC2021★ 3 cited

Efficient algorithm for approximating Nash equilibrium of distributed aggregative games

Gehui Xu, Guanpu Chen, Hongsheng Qi +1

In this paper, we aim to design a distributed approximate algorithm for seeking Nash equilibria of an aggregative game. Due to the local set constraints of each player, projectionb…

math.OC2021

Distributed Mirror Descent Algorithm with Bregman Damping for Nonsmooth Constrained Optimization

Guanpu Chen, Weijian Li, Gehui Xu +1

To solve distributed optimization efficiently with various constraints and nonsmooth functions, we propose a distributed mirror descent algorithm with embedded Bregman damping, as…

math.OC2021★ 3 cited

No-regret distributed learning in subnetwork zero-sum games

Shijie Huang, Jinlong Lei, Yiguang Hong +2

In this paper, we consider a distributed learning problem in a subnetwork zero-sum game, where agents are competing in different subnetworks. These agents are connected through tim…

math.OC2021★ 1 cited

Distributed Variable Sample-size Stochastic Optimization with Fixed Step-sizes

Jinlong Lei, Peng Yi, Jie Chen +1

The paper considers distributed stochastic optimization over randomly switching networks, where agents collaboratively minimize the average of all agents' local expectation-valued…