快速执行器对一类非线性采样数据系统通过确定性学习进行故障耐受性控制
Yu Zeng1, Tianrui Chen1, Fukai Zhang1
1School of Control Science and Engineering, Shandong University, Jinan, 250061, PR China.
ISA transactions
|June 24, 2025
概括
本研究介绍了非线性采样数据系统中快速故障耐受性控制 (FTC) 的确定性学习方法 (DLA). 它可以快速检测,隔离和控制对初始和较大的执行器故障的响应.
科学领域:
- 控制系统工程 控制系统工程
- 非线性动力学是一种非线性动力学.
- 故障诊断和耐受性控制
背景情况:
- 非线性采样数据系统容易发生执行器故障,影响性能和安全.
- 现有的故障耐受性控制 (FTC) 方法可能会与故障从初始到更大规模的快速演变作斗争.
研究的目的:
- 为经历分阶段执行器故障的非线性采样数据系统制定快速耐故障控制策略.
- 为了提高故障检测和隔离 (FDI) 的灵敏度和响应速度,用于初始和重大执行器故障.
主要方法:
- 使用确定性学习方法 (DLA) 来构建学习控制器和识别器.
- 用线性时间变化 (LTV) 离散时间系统的指数稳定性来获得控制和故障诊断知识.
- 基于模式的FTC方案和诊断估计器被用于故障响应.
主要成果:
- 拟议的方法实现了追踪和参数估计错误的同时指数趋同.
- 对初始执行器故障的增强敏感性和对更大的故障的快速FTC响应被证明.
- 模拟结果验证了开发的FDI和FTC计划的有效性.
结论:
- 基于DLA的FTC策略有效地处理非线性采样数据系统中的分阶段执行器故障.
- 该方法提供快速故障检测,隔离和控制适应,提高系统的弹性.
- 该方法提供了一个强大的解决方案,用于提高控制性能和故障条件下的安全性.
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