Abstract
In this paper, an indirect dual ascent method with an exponential convergence rate is proposed for a general resource allocation problem with convex objectives and weighted constraints. By introducing the indirect dual variables, the dual dynamics can be executed in a decentralized manner by all nodes over the network. In contrast to the conventional methods, consensus on all the dual variables is not required. This further leads to the fast convergence, reduced communication burden and better privacy preserving. Moreover, the exponential convergence rate of the proposed algorithm is established through the Lyapunov method and the singular perturbation theory. Application of the dynamic power dispatch problem in smart grid verifies the effectiveness and performance of the proposed algorithm. © Springer Nature B.V. 2020.
| Original language | English |
|---|---|
| Pages (from-to) | 1685-1699 |
| Number of pages | 15 |
| Journal | Nonlinear Dynamics |
| Volume | 102 |
| Issue number | 3 |
| Online published | 25 Aug 2020 |
| DOIs | |
| Publication status | Published - Nov 2020 |
| Externally published | Yes |
Funding
This work is supported by the National Natural Science Foundation of China under Grants 61773172, 61572210 and 51537003, the Natural Science Foundation of Hubei Province of China (2017CFA035), the Fundamental Research Funds for the Central Universities (2018KFYYX-JJ119), the Program for HUST Academic Frontier Youth Team and the 111 Project on Computational Intelligence and Intelligent Control under Grant B18024 and the Australian Research Council under Grant DP170102303.
Research Keywords
- Distributed algorithm
- Dual ascent dynamics
- Exponential convergence
- Resource allocation
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