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We propose a novel distributed control scheme that eliminates the necessity for global communication topology information while ensuring prescribed-time convergence to the global minimizer of the objective function. First, we design a new prescribed-time estimator to compute the average gradients and Hessians of the objective function. Concurrently, we introduce a fully distributed consensus control scheme that enables all agents to achieve consensus. Second, utilizing the estimated gradients and Hessians, and with consensus achieved among the MAS, we develop a prescribed-time optimization controller that ensures the convergence of all agents\u2019 states to the global minimizer. A numerical simulation is included to demonstrate the effectiveness of the proposed control methods.<\/jats:p>","DOI":"10.1142\/s2301385026500299","type":"journal-article","created":{"date-parts":[[2025,3,20]],"date-time":"2025-03-20T04:11:19Z","timestamp":1742443879000},"page":"963-971","source":"Crossref","is-referenced-by-count":0,"title":["Fully Distributed Prescribed-Time Optimization of Multi-Agent Systems"],"prefix":"10.1142","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4165-3764","authenticated-orcid":false,"given":"Yuan","family":"Liu","sequence":"first","affiliation":[{"name":"School of Intelligent Manufacturing, Nanyang Institute of Technology, Nanyang, Henan, P. R. 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