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A Distributed Pre-Defined-Time Solution to Time-Varying Constrained Optimization Problems Over Multiplex Networks
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DOI：10.1109/jas.2026.125816.png)
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Abstract
En 中文
Numerous engineering applications involve optimization with constrained conditions. This study proposes a novel distributed algorithm for solving time-varying (TV) constrained optimization problems over multiplex networks within the predefined time, where both the objective functions and constraints are TV. By integrating a time-regulator function and the supra-Laplacian matrix, we develop an integral sliding mode-based distributed optimization algorithm that guarantees predefined-time convergence. The proposed approach eliminates the need for restrictive state initialization and ensures minimization of the global TV cost function within a user-defined time frame, significantly enhancing applicability. Numerical simulations validate the effectiveness and superiority of the proposed algorithms.
Keywords:
Distributed algorithm
multiplex network
predefined-time convergence
time-varying constrained optimization
Journal
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19.2
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1.4K
Citations:
1.1W