一种新的并行控制方法,用于非线性多代理系统的最佳共识
IEEE transactions on cybernetics
|June 10, 2024
概括
本研究介绍了使用自适应动态编程 (ADP) 在非线性多代理系统 (MAS) 中实现最佳共识的并行控制. 该方法可以在没有系统知识的情况下进行在线学习控制协议,确保信号的融合.
科学领域:
- 控制系统工程 控制系统工程
- 人工智能的人工智能
- 机器人技术 机器人技术 机器人技术
背景情况:
- 多代理系统 (MAS) 在实现协调控制方面存在挑战.
- 传统的控制方法与非线性动态和未知的系统参数作斗争.
- 最佳的共识控制对于有效的MAS运作至关重要.
研究的目的:
- 为连续时间非线性MAS开发一个最佳的共识控制策略.
- 引入与自适应动态编程 (ADP) 集成的并行控制方法.
- 为了使在线学习的控制协议,没有先前的系统知识.
主要方法:
- 将控制输入集成到用于并行控制的反系统中.
- 建立一个具有绩效指数功能的增强系统.
- 政策代算法用于评估控制方案的可行性和趋同.
- 莱普诺夫的方法来证明信号的趋同.
- 实现基于ADP的控制协议的在线学习算法.
主要成果:
- 拟议的并行控制方案实现了非线性MAS的最佳共识控制.
- 政策代算法证明了可行性和趋同.
- 在线学习算法成功实现了基于ADP的控制协议.
- 利亚普诺夫稳定性分析证实了信号的趋同.
- 实验数据验证了理论发现.
结论:
- 开发的基于ADP的最佳并行共识控制对非线性MAS有效.
- 该方法可以在没有事先系统识别的情况下促进在线学习和控制.
- 该方法提供了一个强大的解决方案,用于在复杂的多代理系统中实现协调的行为.
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