典型文献
A Fully Distributed Hybrid Control Framework For Non-Differentiable Multi-Agent Optimization
文献摘要：
This paper develops a fully distributed hybrid con-trol framework for distributed constrained optimization pro-blems.The individual cost functions are non-differentiable and convex.Based on hybrid dynamical systems,we present a dis-tributed state-dependent hybrid design to improve the transient performance of distributed primal-dual first-order optimization methods.The proposed framework consists of a distributed con-strained continuous-time mapping in the form of a differential inclusion and a distributed discrete-time mapping triggered by the satisfaction of local jump set.With the semistability theory of hybrid dynamical systems,the paper proves that the hybrid con-trol algorithm converges to one optimal solution instead of oscil-lating among different solutions.Numerical simulations illustrate better transient performance of the proposed hybrid algorithm compared with the results of the existing continuous-time algo-rithms.
文献关键词：
中图分类号：
作者姓名：
Xia Jiang;Xianlin Zeng;Jian Sun;Jie Chen;Yue Wei
作者机构：
Key Laboratory of Intelligent Control and Decision of Complex Systems,School of Automation,Beijing Institute of Technology,Beijing 100081,and also with the Beijing Institute of Techno-logy Chongqing Innovation Center,Chongqing 401120,China;Key Laboratory of Intelligent Control and Decision of Complex Systems,School of Automation,Beijing Institute of Technology,Beijing 100081,China;School of Electronic and Information Engineering,Tongji University,Shanghai 200082,and also with the Key Laboratory of Intelligent Control and Decision of Complex Systems,School of Automation,Beijing Institute of Technology,Beijing 100081,China;Peng Cheng Laboratory,Shenzhen 518055,China
文献出处：
引用格式：
[1]Xia Jiang;Xianlin Zeng;Jian Sun;Jie Chen;Yue Wei-.A Fully Distributed Hybrid Control Framework For Non-Differentiable Multi-Agent Optimization)[J].自动化学报（英文版）,2022(10):1792-1800
A类：
Differentiable,blems,semistability
B类：
Fully,Distributed,Hybrid,Control,Framework,For,Non,Multi,Agent,Optimization,This,paper,develops,fully,distributed,hybrid,framework,constrained,optimization,individual,cost,functions,differentiable,convex,Based,dynamical,systems,we,present,state,dependent,design,improve,transient,performance,primal,first,order,methods,proposed,consists,continuous,mapping,differential,inclusion,discrete,triggered,by,satisfaction,local,jump,set,With,theory,proves,that,algorithm,converges,one,optimal,instead,oscil,lating,among,solutions,Numerical,simulations,illustrate,better,compared,results,existing,rithms
AB值：
0.574351
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