在错误数据注入攻击和输入和约束下切换非线性系统的自适应性性能控制
Wenjing He1, Youqing Wang1, Yukun Shi1
1State Key Laboratory of Chemical Resource Engineering, and the College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, 100029, China.
概括
本研究介绍了面临虚假数据注入攻击和干扰的非线性系统的自适应控制. 这种新的策略确保了强大的跟踪性能,尽管系统复杂性和和.
科学领域:
- 控制系统工程 控制系统工程
- 非线性动力学是一种非线性动力学.
- 网络安全 网络安全
背景情况:
- 交换非线性系统容易受到虚假数据注入 (FDI) 攻击.
- 隐性干扰和输入和挑战现有的控制和干扰观察方法.
- 当前规定的性能控制在输入和下缺乏有效性.
研究的目的:
- 为在FDI攻击,复合干扰和输入和下切换非线性系统开发适应性性能控制策略.
- 解决现有的干扰观察员在处理隐性干扰方面的局限性.
- 在输入和的情况下克服传统方法的无效性.
主要方法:
- 一个新的切换非线性干扰观察者使用动态高增益来重建隐式不匹配的干扰.
- 一个适应性更新法来补偿匹配的干扰.
- 一个修改的固定时间性能功能,以平衡输入和和跟踪性能.
- 在后退控制中进行神经网络近似,以减轻外国直接投资的攻击效应.
主要成果:
- 建议的干扰观察器有效地重建隐含的不匹配干扰.
- 适应性更新法成功地补偿了匹配的干扰.
- 修改后的性能功能平衡了输入和和跟踪.
- 神经网络的近似减轻了外国直接投资的攻击影响.
- 模拟结果表明有效的跟踪控制.
结论:
- 开发的自适应性性能控制策略有效地管理在FDI攻击,复合干扰和输入和下切换非线性系统.
- 新的干扰观察员和自适应控制技术提高了系统的弹性和性能.
- 该战略为复杂的控制场景提供了灵活而强大的解决方案.
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