Abstract
This article addresses the distributed prescribed-time convex optimization (DPTCO) problem for high-order nonlinear multiagent systems (MASs) under undirected connected graphs. A cascade design framework is proposed that divides the DPTCO implementation into distributed optimal trajectory generator design and local reference trajectory tracking controller design. The DPTCO problem is then transformed into the prescribed-time stabilization problem of a cascaded system. Using changing Lyapunov functions and time-varying state transformations with sufficient conditions, we establish criteria for prescribed-time stabilization and prove the boundedness of internal signals in closed-loop MASs. The framework addresses robust DPTCO for chain-integrator MASs with disturbances through the introduction of novel sliding-mode variables and time-varying gains. It also solves adaptive DPTCO for strict-feedback MASs with parameter uncertainty via backstepping method and descending power state transformation. Two numerical examples verify the theoretical results.
| Original language | English |
|---|---|
| Pages (from-to) | 4784-4797 |
| Number of pages | 14 |
| Journal | IEEE Transactions on Cybernetics |
| Volume | 55 |
| Issue number | 10 |
| Early online date | 29 Aug 2025 |
| DOIs | |
| Publication status | Published - Oct 2025 |
| Externally published | Yes |
Bibliographical note
Publisher Copyright:© 2013 IEEE.
Funding
This work was supported in part by the National Natural Science Foundation of China under Grant 62173155 and Grant 52188102; in part by the Program for Huazhong University of Science and Technology (HUST) Academic Frontier Youth Team; and in part by the Taihu Lake Innovation Fund for Future Technology, HUST.
Keywords
- distributed convex optimization (DCO)
- prescribed-time control
- stabilization of cascaded systems
- time-varying gains