通过模糊的神经自适应滑动控制,高阶非线性多代理系统的规定的时间领袖-追随者同步
Safeer Ullah1, Muhammad Zeeshan Babar2, Sultan Alghamdi3,4
1Department of Electrical Engineering, Quaid-e-Azam College of Engineering & Technology, Sahiwal 57000, Pakistan.
Sensors (Basel, Switzerland)
|December 31, 2025
概括
本研究提出了一个新的控制框架,用于在设定的时间内更快,更稳定的非线性多代理系统 (MAS) 的同步. 它使用模糊的神经网络和自适应控制来有效处理不确定性和干扰.
科学领域:
- 控制理论 控制理论
- 人工智能的人工智能
- 系统工程 系统工程
背景情况:
- 多代理系统 (MAS) 的同步对于协调行为至关重要.
- 现有的方法在不确定性下与规定的时间控制作斗争.
研究的目的:
- 开发一种新的控制框架,用于非线性MAS的规定的时间同步.
- 确保领导者和追随者在用户定义的时间内达成共识,无论最初的状态如何.
主要方法:
- 模糊神经网络 (FNN) 的集成用于在线非线性近似.
- 使用一个强大的非单元终端滑动模式控制器 (NTSMC).
- 采用自适应更新定律和利亚普诺夫稳定性分析.
主要成果:
- 实现了对高阶非线性MAS的规定的时间同步.
- 证明了对参数不确定性和外部干扰的增强强性.
- 与传统方法相比,模拟证实了更快的融合和适应性.
结论:
- 拟议的FNN-NTSMC框架为MAS同步提供了卓越的性能.
- 对不确定性和干扰的有效处理确保了可靠的共识.
- 该方法在用户定义的时间框架内提供精确的控制.
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