Paper Info
Title
Distributed Nonsmooth Optimization with Consensus and Inequality Constraints via Distributed Smooth Proximal-Splitting Algorithm
Abstract
This paper investigates a class of distributed nonsmooth optimization problems with consensus and inequality constraints. Each local cost function contains a smooth convex function and two nonsmooth convex functions. Moreover, consensus needs to be achieved at the optimal solution of these problems. With the help of splitting method, a distributed smooth proximal-splitting algorithm is proposed in this paper. The convergence analysis of this algorithm is conducted by employing Lyapunov stability theory and the property of proximal operator. Combining with simulation results, it is shown that the multi-agent system steered by the proposed algorithm can reach consensus on the optimal point while satisfying inequality constraints.
Year
DOI
Venue
2020
10.1109/ICCA51439.2020.9264474
2020 IEEE 16th International Conference on Control & Automation (ICCA)
Keywords
DocType
ISSN
inequality constraints,smooth convex function,nonsmooth convex functions,Lyapunov stability theory,distributed nonsmooth optimization,distributed smooth proximal splitting algorithm,convergence analysis,multiagent system
Conference
1948-3449
ISBN
Citations 
PageRank 
978-1-7281-9094-5
0
0.34
References 
Authors
10
4
Name
Order
Citations
PageRank
Wei Yue117015.50
hao fang2478.32
Dou Lihua314513.33
Qingkai Yang4226.51