适应性神经事件触发的容错控制不确定非线性网络物理系统通过触发输出反传感器和执行器故障通过触发输出反
IEEE transactions on cybernetics
|June 18, 2025
概括
本研究介绍了针对不确定的非线性网络物理系统 (CPS) 的自适应性神经事件触发故障耐受性控制 (FTC). 拟议的方案确保了系统稳定性和输出融合,同时最大限度地降低了计算负载.
科学领域:
- 控制系统工程 控制系统工程
- 网络物理系统 网络物理系统
- 人工智能的人工智能
背景情况:
- 网络物理系统 (CPS) 面临来自未知的动态和故障的挑战.
- 容错控制 (FTC) 对于保持系统稳定性和性能至关重要.
- 事件触发机制通过减少数据传输和计算来提高效率.
研究的目的:
- 为不确定的非线性CPS开发一个自适应的神经事件触发输出反FTC方案.
- 为了解决未知的系统动态,传感器和执行器同时发生故障.
- 通过事件触发方法来减少计算负担.
主要方法:
- 事件触发机制与一级过器和非线性冲动动态相结合.
- 适应性神经网络用于状态估计和控制.
- 输出,状态估计和控制器更新的双触发条件.
- 神经状态观察者设计使用触发错误输出.
主要成果:
- 所有闭环信号都是有界的.
- 系统输出与原始交汇.
- 实际上,Zeno的行为被排除在外.
- 模拟结果验证了该计划的可行性和有效性.
结论:
- 拟议的自适应神经事件触发FTC方案提高了不确定的非线性CPS的稳定性和效率.
- 该方法成功地处理了系统的不确定性和各种故障类型.
- 事件触发策略显著降低了计算负载,而不会影响性能.
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