基于观察者的H H
Xuelin Zhang1, Xiaobin Xu1, Jianning Li2
1China-Austria Belt and Road Joint Laboratory on Artificial Intelligence and Advanced Manufacturing, Hangzhou Dianzi University, Hangzhou 310018, China; School of Automation, Hangzhou Dianzi University, Hangzhou 310018, Zhejiang, China.
ISA transactions
|June 9, 2023
概括
这项研究引入了船舶自动驾驶系统的先进模糊故障耐受性控制,提高了对故障和未测量状态的航向跟踪稳定性. 该方法有效地估计和补偿转向机器故障,确保更安全的导航.
科学领域:
- 海洋工程 海洋工程
- 控制系统 控制系统
- 模糊的逻辑 模糊的逻辑
背景情况:
- 船舶自动驾驶 (SA) 系统需要加强对非线性动力学,未测量状态和转向机器故障的稳定性.
- 现有的控制方法可能无法充分解决现实世界船舶导航和潜在系统故障的复杂性.
研究的目的:
- 为船舶航线跟踪提出一个基于观察者的H∞模糊的容错切换控制策略.
- 提高船舶自动驾驶系统的稳定性和可靠性.
主要方法:
- 开发了一个全球的Takagi-Sugeno (T-S) 模糊非线性船舶自动驾驶 (NSA) 模型,该模型与真实导航数据进行了验证.
- 虚拟模糊观察器 (VFO) 的设计,用于同时估计未测量状态和未知的故障.
- 实施基于Z分数的平滑故障检测和报警 (FDA) 控制器切换.
主要成果:
- 拟议的VFO有效地估计未测量状态和未知的故障,使故障系统的补偿成为可能.
- 基于VFO的H∞稳固控制器 (VFO-HRC) 和耐故障控制器 (VFO-HFTC) 被设计和集成.
- 在"玉龙"号船上的模拟结果证明了故障耐受开关控制方法的有效性.
结论:
- 开发的基于观察者的H∞模糊故障耐受开关控制器增强了船舶自动驾驶员的稳定性.
- 该方法成功地解决了非线性动力学,未测量状态和未知的方向盘机器故障.
- 这种方法提供了一个可靠的解决方案,用于在故障条件下跟踪船舶航线.
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