activity
20192022
most citedPrescribed-Time Fully Distributed Nash Equilibrium Seeking in Noncooperative Games

8 citations · 31 across the 10 of their papers we have counts for

collaborators

20 papers

math.OC20222 cited

Distributed Optimization with Coupling Constraints in Multi-Cluster Networks Based on Dual Proximal Gradient Method

Jianzheng Wang, Guoqiang Hu

In this work, we consider solving a distributed optimization problem in a multi-agent network with multiple clusters. In each cluster, the involved agents cooperatively optimize a…

math.OC20212 cited

Distributed Generalized Nash Equilibrium Seeking of N-Coalition Games with Full and Distributive Constraints

Chao Sun, Guoqiang Hu

In this work, we investigate the distributed generalized Nash equilibrium (GNE) seeking problems for -coalition games with inequality constraints. First, we study the scenario w…

eess.SY2021

Social Cost Optimization for Prosumer Community with Two Price-Package Incentives in Two-Settlement Based Electricity Market

Jianzheng Wang, Guoqiang Hu

In this paper, we consider a future electricity market consisting of aggregated energy prosumers, who are equipped with local wind power plants (WPPs) to support (part of) their en…

eess.SY2021

Resilient Time-Varying Output Formation Tracking of Linear Multi-Agent Systems Against Unbounded FDI Sensor Attacks and Unreliable Digraphs

Zhi Feng, Guoqiang Hu

One salient feature of cooperative formation tracking is its distributed nature that relies on localized control and information sharing over a sparse communication network. That i…

math.OC2021

Attack-Resilient Distributed Convex Optimization of Linear Multi-Agent Systems Against Malicious Cyber-Attacks over Random Digraphs

Zhi Feng, Guoqiang Hu

This paper addresses a resilient exponential distributed convex optimization problem for a heterogeneous linear multi-agent system under Denial-of-Service (DoS) attacks over random…

math.OC2021

A Gradient-Free Distributed Optimization Method for Convex Sum of Non-Convex Cost Functions

Yipeng Pang, Guoqiang Hu

This paper presents a special type of distributed optimization problems, where the summation of agents' local cost functions (i.e., global cost function) is convex, but each indivi…