Cooperative Tuning of Multi-Agent Optimal Control Systems
Abstract
This paper investigates the problem of cooperative tuning of multi-agent optimal control systems, where a network of agents (i.e. multiple coupled optimal control systems) adjusts parameters in their dynamics, objective functions, or controllers in a coordinated way to minimize the sum of their loss functions. Different from classical techniques for tuning parameters in a controller, we allow tunable parameters appearing in both the system dynamics and the objective functions of each agent. A framework is developed to allow all agents to reach a consensus on the tunable parameter, which minimizes team loss. The key idea of the proposed algorithm rests on the integration of consensus-based distributed optimization for a multi-agent system and a gradient generator capturing the optimal performance as a function of the parameter in the feedback loop tuning the parameter for each agent. Both theoretical results and simulations for a synchronous multi-agent rendezvous problem are provided to validate the proposed method for cooperative tuning of multi-agent optimal control.
Cite
@article{arxiv.2209.12017,
title = {Cooperative Tuning of Multi-Agent Optimal Control Systems},
author = {Zehui Lu and Wanxin Jin and Shaoshuai Mou and Brian D. O. Anderson},
journal= {arXiv preprint arXiv:2209.12017},
year = {2022}
}