Distributed Online Optimization for Multi-Agent Networks With Coupled Inequality Constraints

• 成果类型: Article
• 署名作者: Li, Xiuxian; Yi, Xinlei; Xie, Lihua
• 署名单位: Nanyang Technological University; Royal Institute of Technology
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2020.3021011
• 发表日期: 2021
• 页码: 3575-3591
• 关键词: Cost function; Heuristic algorithms; Vehicle dynamics; Task analysis; STANDARDS; power systems; Coupled inequality constraints; Distributed online optimization; multi-agent networks; primal-dual; push-sum

摘要

This article investigates the distributed online optimization problem over a multi-agent network subject to local set constraints and coupled inequality constraints, which has a lot of applications in many areas, such as wireless sensor networks, power systems, and plug-in electric vehicles. In this problem, the cost function at each time step is the sum of local cost functions with each of them being gradually revealed to its corresponding agent, and meanwhile only local functions in coupled inequality constraints are accessible to each agent. To address this problem, a modified primal-dual algorithm, called distributed online primal-dual push-sum algorithm, is developed in this article, which does not rest on any assumption on parameter boundedness and is applicable to unbalanced networks. It is shown that the proposed algorithm is sublinear for both the dynamic regret and the violation of coupled inequality constraints. Finally, the theoretical results are supported by a simulation example.