A Continuous-Time Distributed Optimization Algorithm for Multi-Agent Systems with Parametric Uncertainties over Unbalanced Digraphs

Qing Yang () and Caiqi Jiang
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Qing Yang: School of Information Science and Engineering, Chongqing Jiaotong University, Chongqing 400074, China
Caiqi Jiang: School of Information Science and Engineering, Chongqing Jiaotong University, Chongqing 400074, China

Mathematics, 2025, vol. 13, issue 16, 1-16

Abstract: This paper investigates distributed optimization problems for multi-agent systems with parametric uncertainties over unbalanced directed communication networks. To settle this class of optimization problems, a continuous-time algorithm is proposed by integrating adaptive control techniques with an output feedback tracking protocol. By systematically employing Lyapunov stability theory, perturbed system analysis, and input-to-state stability theory, we rigorously establish the asymptotic convergence property of the proposed algorithm. A numerical simulation further demonstrates the effectiveness of the algorithm in computing the global optimal solution.

Keywords: distributed optimization; continuous-time algorithm; unbalanced directed networks; adaptive control; parametric uncertainties (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
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