@inproceedings{9d3305ab02784a87ac76c785d15b0ddb,
title = "Distributed convex nonsmooth optimization for multi-agent system based on proximal operator",
abstract = "This paper considers a class of distributed non-differentiable convex optimization problems, in which each local cost function is composed of a twice differentiable convex function and a lower semi-continuous convex function. Motivated by the proximal operator and derivative feedback methods, continuous distributed optimization algorithms for both single-integrator and double-integrator multi-agent systems are developed to achieve distributed optimal consensus. Finally, simulation results are provided to illustrate the effectiveness of the proposed methods.",
keywords = "Distributed optimization, Multi-agent systems, Non-differentiable convex optimization, Proximal operator",
author = "Qing Wang and Xianlin Zeng and Bin Xin and Jie Chen",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 15th IEEE International Conference on Control and Automation, ICCA 2019 ; Conference date: 16-07-2019 Through 19-07-2019",
year = "2019",
month = jul,
doi = "10.1109/ICCA.2019.8899755",
language = "English",
series = "IEEE International Conference on Control and Automation, ICCA",
publisher = "IEEE Computer Society",
pages = "1085--1090",
booktitle = "2019 IEEE 15th International Conference on Control and Automation, ICCA 2019",
address = "United States",
}