Distributed constrained optimization using a projected differential inclusion

Xianlin Zeng, Peng Yi, Jie Chen

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper designs a distributed algorithm for large-scale constrained optimization problems, where the agents cooperate with each other based on local information and communication information. The objective functions may be nonmsooth and the variable is subject to set constraints. This paper proposes a distributed continuous-time solver based on stability theory and optimization theory. The designed projected differential inclusion has solutions even though it is nonconvex and its convergence to one of solutions to the optimization problem is proved rigorously. The projected differential design may also be applied to other more general optimization problems and the methodology is illustrated through a numerical simulation.

Original languageEnglish
Title of host publication2018 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages337-342
Number of pages6
ISBN (Electronic)9781538668689
DOIs
Publication statusPublished - 2 Jul 2018
Event2018 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2018 - Kandima, Maldives
Duration: 1 Aug 20185 Aug 2018

Publication series

Name2018 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2018

Conference

Conference2018 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2018
Country/TerritoryMaldives
CityKandima
Period1/08/185/08/18

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