Abstract
This paper investigates the distributed optimization problem for multi-agent systems. An adaptive algorithm with edge-event-based triggering is proposed to minimize a differential global objective function. It is shown that the proposed algorithm can ensure that the consensus error is asymptotically stabilized and the Zeno behaviour can be avoided. Moreover, a sampled-data scheme driven by edge-events is proposed to relax the requirement of continuous communication between neighbouring agents without the need of global information.
| Original language | English |
|---|---|
| Title of host publication | 2019 Chinese Control Conference (CCC) |
| Publisher | IEEE |
| Pages | 6038-6043 |
| ISBN (Electronic) | 978-9-8815-6397-2 |
| ISBN (Print) | 978-1-7281-2329-5 |
| DOIs | |
| Publication status | Published - Jul 2019 |
| Event | 38th Chinese Control Conference, CCC 2019 - Guangzhou Baiyun International Convention Center, Guangzhou, China Duration: 27 Jul 2019 → 30 Jul 2019 http://www.ccc2019.cn/index.html |
Publication series
| Name | Chinese Control Conference, CCC |
|---|---|
| Publisher | IEEE |
| ISSN (Print) | 1934-1768 |
| ISSN (Electronic) | 2161-2927 |
Conference
| Conference | 38th Chinese Control Conference, CCC 2019 |
|---|---|
| Place | China |
| City | Guangzhou |
| Period | 27/07/19 → 30/07/19 |
| Internet address |
Research Keywords
- Adaptive control
- Distributed optimization
- Edge-events
- Multi-agent systems
Fingerprint
Dive into the research topics of 'Distributed Adaptive Optimization Via Edge-event-based Triggering'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver