Abstract
Event-triggered sampling and control provides an effective solution to actively acquire measurement information and selectively perform estimation or control updates for enhanced system performance. In this chapter, we provide a concise overview of event-triggered state estimation and control developed for networked systems with limited communication or computation resources, as well as the recent developments on event-triggered learning that enable active discovery of system dynamics with enhanced data efficiency. Key technical challenges, major developments, and potential future directions are also discussed.
| Original language | English |
|---|---|
| Title of host publication | Encyclopedia of Systems and Control Engineering |
| Publisher | Elsevier |
| Pages | 297-308 |
| ISBN (Electronic) | 9780443140815 |
| ISBN (Print) | 9780443140808 |
| DOIs | |
| Publication status | Published - 2026 |
Bibliographical note
Publisher Copyright:© 2026 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
Keywords
- Event-triggered control
- Learning-based control
- Networked control systems
- State estimation
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