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Distributed Protocols for Constrained Optimization of Integrator Chain Multiagent Systems
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AI
DOI：10.1109/TAC.2024.3394128.png)
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Abstract
En 中文
This article studies the constrained optimization problem of integrator chain multiagent systems from the distributed perspective. Particularly, all the agents collaborate to find an optimal solution of a global objective function summed by multiple local ones, each of which is just convex and belongs to an individual agent. However, the potential optimal solutions are simultaneously subject to set constraints and two kinds of equality constraints, i.e., individual equality constraint and aggregate equality constraint, whereas their involved constraint parameters are privately available to individual agents. With a proper coordinate transformation, a distributed optimization protocol is synthesized by introducing proper internal dynamics. Under the Lyapunov framework, it is shown with a convex theory that the synthesized distributed protocol enables the multiagent system to achieve the concerned constrained optimization objective. An example is finally given to confirm the optimization effectiveness.
Keywords:
Optimization
Protocols
Multi-agent systems
Linear programming
STEM
Aggregates
Decision feedback equalizers
Constrained optimization
distributed protocol
equality constraint
integrator chain system
set constraint
Journal
IF:
7
Papers:
1.3W
Citations:
6.7W
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