对非线性系统进行联合状态和故障估计,受测量审查和缺失测量
Yudong Wang1, Tingting Guo2, Xiaodong He3
1College of Mechanical and Electrical Engineering, Qingdao Agricultural University, Qingdao 266109, China.
Sensors (Basel, Switzerland)
|September 13, 2025
概括
这项研究引入了一种用于估计非线性系统中系统状态和故障的新方法,这些系统面临测量审查和缺失数据. 这种方法可以确保即使是复杂的数据问题,也能得到可靠的估计.
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
- 信号处理 信号处理
背景情况:
- 对于非线性系统,由于测量审查 (MC) 和缺失测量 (MMs),对状态估计具有挑战性.
- 执行器故障进一步使动态系统中的准确状态估计变得复杂.
- 现有的方法经常与MC和MM的组合作斗争,需要先进的估计技术.
研究的目的:
- 为非线性系统开发一种新的联合状态和故障估计框架.
- 为应对同时测量审查和随机丢失测量的挑战.
- 为了使系统状态和执行器故障信号的可靠和同时估计.
主要方法:
- 集成一个改进的托比特·卡尔曼过器来模拟测量审查.
- 使用伯努利随机变量来描述随机缺失的测量.
- 在分布式估计和集中式聚变中应用联合聚变方法.
- 在估计框架内考虑突发和坡道执行器故障.
主要成果:
- 提出了一个新的联合估计框架,将托比特·卡尔曼过和联合融合结合起来.
- 该框架实现了系统状态和故障信号的同时可靠估计.
- 设计估计器的过误差的局限性在特定条件下被证明.
- 通过两个工程实验证明了有效性.
结论:
- 拟议的框架有效地处理与测量审查和缺失测量的非线性系统.
- 整合托比特过和联合融合为联合状态和故障估计提供了强大的解决方案.
- 该方法在复杂和杂的环境中为状态估计提供了更高的可靠性.
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