Distributed Asynchronous Time-Varying Quadratic Programming With Asynchronous Objective Sampling

• 成果类型: Article
• 署名作者: Behrendt, Gabriel; Bell, Zachary I.; Hale, Matthew
• 署名单位: University System of Georgia; Georgia Institute of Technology
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2026.3654317
• 发表日期: 2026
• 关键词: convex-optimization; real-time; CONVERGENCE; algorithm

摘要

Existing works on multiagent time-varying optimization allow agents to asynchronously communicate and/or compute, but do not allow asynchronous sampling of objectives. Sampling can be difficult to synchronize, and we therefore present a multiagent optimization framework that allows asynchrony in sampling, communications, and computations for time-varying quadratic programs. We show that agents have bounded error when tracking the solution to the asynchronously sampled problem, which solves an open problem for quadratic programs. Simulations validate these results.