Event-triggered distributed optimization for multi-agent systems with quantization and disturbance rejection
Abstract
Abstract In this paper, adaptive continuous-time algorithms with event-triggered mechanism are studied to solve the optimization problem. First, an event-triggered adaptive algorithm is introduced, and it is proven that this algorithm can effectively solve the optimization problem. Second, to solve the optimization problem, two event-triggered algorithms are proposed, one considering uniform quantization information and the other addressing external disturbances. It is demonstrated that the states of the multi-agent systems practically converge to the global optimal point. Three numerical cases demonstrate the effectiveness of the relevant results.
Fields of Study & Subjects
Distributed Control Multi-Agent Systems
Adaptive Dynamic Programming Control
Extremum Seeking Control Systems
Publication details
- Journal / source
- IMA Journal of Mathematical Control and Information
- Publisher
- Oxford University Press (OUP)
- Volume
- 43
- Issue
- 1
- Publication date
- 9 January 2026
- Language
- EN