Abstract
In this paper, a distributed optimization algorithm is proposed for aggregative game with coupled constraints. Based on the singular perturbation system, the generalized Nash equilibrium is sought by a group of agents. By employing the average consensus method in the fast manifold, the aggregates in the object function can be estimated via simple information exchanges, as well as the aggregate of dual variables, which provides necessary information for the fully distributed algorithm design. Moreover, the exponential convergence of the proposed algorithm is explored based on the Lyapunov method, the properties of the variational inequality and the characteristic of the singular perturbation system. Application to the resource competition problem in smart grid verifies the effectiveness of the proposed algorithm. © 2021 Elsevier B.V.
| Original language | English |
|---|---|
| Pages (from-to) | 278-286 |
| Journal | Neurocomputing |
| Volume | 482 |
| Online published | 26 Nov 2021 |
| DOIs | |
| Publication status | Published - 14 Apr 2022 |
| Externally published | Yes |
Funding
This work is supported by the National Natural Science Foundation of China under Grant 62073344.
Research Keywords
- Coupled constraints
- Distributed optimization
- Nash equilibrium
- Smart grid
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