Abstract
In this paper, we address time-varying resource allocation problems with heterogeneous Hessian matrices across agents. A novel prescribed-time convergent algorithm is proposed by integrating distributed average consensus estimators and a prediction-correction method. The global convergence is rigorously established via Lyapunov analysis. Numerical simulations on a battery energy storage system demonstrate the algorithm's effectiveness in achieving optimal resource allocation within user-defined time horizons.
| Original language | English |
|---|---|
| Pages (from-to) | 37-41 |
| Number of pages | 5 |
| Journal | Youth Academic Annual Conference of Chinese Association of Automation, YAC |
| Issue number | 2025 |
| DOIs | |
| State | Published - 2025 |
| Event | 40th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2025 - Zhengzhou, China Duration: 17 May 2025 → 19 May 2025 |
Keywords
- Distributed resource allocation
- Prescribed-time convergence
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