Distributed formation control for a cooperative multi-agent system using potential function and extremum seeking algorithm

Heng Li, Jun Peng, J. Xiao, Feng Zhou, Weirong Liu, Jing Wang
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引用次数: 5

Abstract

The formation control and communication optimization problem of a multi-agent system is considered in this article. A classical approach for the formation control problem is potential function method. With potential function, agents are kept a given separation distance with neighbors. Since communication quality will generally change due to the physical environment during formation, a given separation distance might not always be the desired communication distance. In this paper, a distributed scheme integrating potential function and extremum seeking algorithm is proposed to obtain the desired separation distance between neighboring agents in real-time. A comprehensive performance index related to the environment is presented first, capturing a trade-off between formation tasks and communication quality. Since it is difficult to predict the gradient of the performance in physical environments, an adaptive model-free extremum seeking algorithm is developed, which calls for no knowledge of the gradient of the performance. Then the desired separation distance can be obtained dynamically by maximizing the performance with extremum seeking algorithm. Simulation results demonstrate effectiveness of the proposed scheme.
基于势函数和极值搜索算法的协同多智能体系统分布式编队控制
研究了多智能体系统的编队控制和通信优化问题。求解编队控制问题的经典方法是势函数法。利用势函数,agent与邻居保持一定的分离距离。由于在形成过程中,通信质量通常会因物理环境的变化而发生变化,因此给定的分离距离可能并不总是理想的通信距离。本文提出了一种将势函数与极值搜索算法相结合的分布式方案,以实时获得相邻agent间所需的分离距离。首先提出了一个与环境相关的综合性能指标,在编队任务和通信质量之间进行权衡。针对物理环境中性能梯度难以预测的问题,提出了一种不需要知道性能梯度的自适应无模型极值搜索算法。然后利用极值搜索算法实现性能的最大化,从而动态获得所需的分离距离。仿真结果验证了该方案的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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