基于面具的保护隐私的自适应双方模糊共识控制,用于马科维亚切换拓学的随机非线性多代理系统
Xisheng Zhan1, Xin Li1, Jie Wu1
1College of Electrical Engineering and Automation, Hubei Normal University, Huangshi 435002, China.
ISA transactions
|January 20, 2026
概括
本研究介绍了使用自适应模糊逻辑的随机非线性多代理系统 (SNMAS) 的隐私保护共识方法. 这种方法确保了强大的共识,即使在不断变化的网络结构和不平衡的连接.
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
- 网络化系统 网络化系统
背景情况:
- 多代理系统 (MAS) 面临着在动态条件下以及隐私问题下达成共识的挑战.
- 随机非线性和马科维切换拓学复杂化了MAS的控制设计.
- 现有的共识协议往往缺乏强大的隐私保护和适应网络变化的能力.
研究的目的:
- 为隐私保护的随机非线性多代理系统 (SNMAS) 开发一个适应性的双边模糊共识战略.
- 为了解决未知的非线性,并确保代理人的初始状态隐私.
- 处理随机拓变化和结构不平衡的签名图.
主要方法:
- 一种基于观察者的控制策略,利用自适应模糊逻辑系统 (FLS) 来近似未知的非线性.
- 一个消失的亲戚面具功能,用于保护代理人的初始状态隐私.
- 使用连续时间马尔科夫过程建模拓变化,并通过固定类型补偿将该方法扩展到不平衡的签名图形.
主要成果:
- 证明了所有闭环系统信号的均终极边界性.
- 尽管存在随机干扰和非线性,但实现了实际的双边共识.
- 成功地将共识协议扩展到结构不平衡的签署图表,保持趋同保证.
结论:
- 拟议的自适应模糊共识策略有效地提高了SNMAS中的隐私和稳定性.
- 该方法为复杂,动态和对隐私敏感的多代理网络中的共识问题提供了可行的解决方案.
- 数字模拟验证了该方法的理论发现和实际适用性.
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