对于具有多传感器故障的未知非线性系统,基于合作批判性学习的安全跟踪控制
IEEE transactions on cybernetics
|October 30, 2024
概括
本研究介绍了基于合作关键学习的安全跟踪控制 (CLSTC) 对于有传感器故障的非线性系统. 该方法有效处理故障,确保系统稳定性和最佳性能.
科学领域:
- 控制系统工程 控制系统工程
- 非线性系统分析 非线性系统分析
- 耐故障控制控制的控制方式
背景情况:
- 未知的非线性系统容易发生多传感器故障,损害跟踪控制性能.
- 现有的方法可能难以在线识别系统动态和同时检测故障.
研究的目的:
- 为面临多传感器故障的未知非线性系统开发基于合作关键学习的安全跟踪控制 (CLSTC) 方法.
- 为了实现强大和最佳的安全跟踪控制,增强故障耐受性.
主要方法:
- 一个低通波器将传感器故障转化为伪执行器故障.
- 一个联合的神经网络Luenberger观察员 (NNLO) 在线估计系统动态和故障.
- 一个增强的跟踪系统和一个新的成本功能被设计为最佳的控制.
- 汉密尔顿 - 雅各比 - 贝尔曼方程是通过适应性批评结构来解决的.
主要成果:
- 拟议的CLSTC方法证明了针对各种传感器故障的有效容错.
- 利亚普诺夫稳定定理证实了所有闭环系统信号的收.
- 模拟结果验证了控制策略的实际适用性和性能.
结论:
- 开发的CLSTC方法为在具有多传感器故障的非线性系统中安全跟踪控制提供了强大的解决方案.
- 该方法有效地整合了在线故障识别和自适应控制,以提高系统可靠性.
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