Extended Zero-Gradient-Sum Approach for Constrained Distributed Optimization with Free Initialization
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ID: 283352
2023
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Abstract
This paper proposes an extended zero-gradient-sum (EZGS) approach for solving
constrained distributed optimization (DO) with free initialization. A
Newton-based continuous-time algorithm (CTA) is first designed for general
constrained optimization and then extended to solve constrained DO based on the
EZGS method. It is shown that for typical consensus protocols, the EZGS CTA can
achieve the performance with exponential/finite/fixed/prescribed-time
convergence. Particularly, the nonlinear consensus protocols for finite-time
EZGS algorithms can have heterogeneous power coefficients. The prescribed-time
EZGS dynamics is continuous and uniformly bounded, which can achieve the
optimal solution in one stage. Moreover, the barrier method is employed to
tackle the inequality constraints. Finally, the performance of the proposed
algorithms is verified by numerical examples.
| Reference Key |
xu2023extended
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|---|---|
| Authors | Xinli Shi; Xinghuo Yu; Guanghui Wen; Xiangping Xu |
| Journal | arXiv |
| Year | 2023 |
| DOI |
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