在恶意威胁下,基于PT-SMC的新型网络物理机器人系统的弹性控制
Yun-Peng Ding1, Chun-Wu Yin1, Saleem Riaz2
1College of information and control engineering, Xi'an University of architecture and technology, Xi'an, Shaanxi 710055, China.
ISA transactions
|August 6, 2025
概括
本研究介绍了机器人网络物理系统 (CPS) 的滑动模式弹性控制策略,以保证在网络攻击下的性能. 该方法确保精确的轨迹跟踪,即使在不确定的初始条件和恶意攻击的情况下.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 控制系统工程 控制系统工程
- 网络安全 网络安全
背景情况:
- 网络物理系统 (CPS) 由于拒绝服务 (DoS) 和虚假数据注入 (FDI) 等网络攻击而面临性能下降.
- 传统的控制策略在不确定的初始条件和动态的网络威胁下往往难以保证性能.
研究的目的:
- 为在多次网络攻击下不确定的机器人CPS开发具有预定义时间融合 (PTC) 的滑动模式 (SM) 弹性控制策略.
- 提高CPS对各种网络攻击的弹性和轨迹跟踪精度.
- 设计一个独立于初始状态的控制策略,确保无论初始条件如何,都能保持一致的性能.
主要方法:
- 对CPS控制信号的网络攻击机制 (乘法和加法) 的分析.
- 设计一个初始值的错误转换函数 (ECF),将任意初始错误映射到规定的邻里.
- 使用改进的极端学习机器 (ELM) 来近似不确定性和网络攻击.
- 整合PTC滑动模式表面 (SMS) 与增强的规定的性能控制 (PPC) 战略.
主要成果:
- 理论分析证实了闭环系统的预定义时间收 (PTC).
- 数字模拟表明,在不同的攻击场景下,轨迹跟踪错误 (TTE) 在指定的时间框架内趋同.
- 在所有初始状态中实现了高跟踪精度 (0.00013rad),验证了战略的稳定性.
结论:
- 拟议的滑动模式弹性控制策略有效地保证了性能,并确保了网络攻击下机器人CPS的预定义时间趋同.
- 独立于初始状态的方法通过消除对初始错误大小的依赖来提高实际应用性.
- 该算法表现出对网络攻击的强大稳定性,使其适合于现实世界的工程应用.
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