Event-triggered distributed optimization for multi-agent systems with quantization and disturbance rejection
Shanshan Qi, Zhiqiang Zhang, Fei Hao, Zehuan Lu, Yuangong Sun
Source record
Source: Crossref
Published: Jan 9, 2026
DOI: 10.1093/imamci/dnag001
Open original source ↗Source abstract
Abstract In this paper, adaptive continuous-time algorithms with event-triggered mechanism are studied to solve the optimization problem. First, an event-triggered adaptive algorithm is introduced, and it is proven that this algorithm can effectively solve the optimization problem. Second, to solve the optimization problem, two event-triggered algorithms are proposed, one considering uniform quantization information and the other addressing external disturbances. It is demonstrated that the states of the multi-agent systems practically converge to the global optimal point. Three numerical cases demonstrate the effectiveness of the relevant results.
Evidence graph
No public relationships recorded yet.
Integrity note: This page is a factual metadata record created by deterministic ingestion. It is not a claim that the work moves a mathematical frontier or has been independently verified.