智能故障耐受性控制使用长期短期内存,在故障条件下提供高效的系统性能
Mostafa H El-Mahdy1, Abdelrahman O Ali2,3, O H Hassan2,3
1Mechatronics Department, Faculty of Engineering, Ahram Canadian University, Cairo, Egypt. mostafa.hamdy@acu.edu.eg.
Scientific reports
|May 9, 2025
概括
本研究介绍了一个数据驱动的故障耐受性控制系统,使用单个长短期存储器 (LSTM) 网络. 这种创新方法提高了控制系统的弹性,而不需要诊断或过程模型,在模拟中证明有效.
科学领域:
- 控制系统工程 控制系统工程
- 在工程领域的人工智能.
- 数据驱动的控制控制数据驱动的控制
背景情况:
- 耐故障控制 (FTC) 对于系统稳定性和故障条件下的性能至关重要.
- 传统的FTC方法通常依赖于复杂的诊断和过程模型.
- 需要数据驱动的方法来简化容错性.
研究的目的:
- 开发和验证一个新的数据驱动的耐故障控制系统.
- 证明一个单一的长短期内存 (LSTM) 网络的有效性,用于集成故障诊断和控制重新配置.
- 消除在FTC系统中对明确诊断和过程模型的要求.
主要方法:
- 基于单一长期短期存储器 (LSTM) 网络的故障耐受性控制系统的实施.
- 通过模拟和验证的数字双胞胎概念与MATLAB集成.
- 在装配器案例研究中应用和测试无故障和故障传感器场景.
主要成果:
- 基于LSTM的系统在出现故障时成功管理了控制重新配置.
- 模拟在6553次代后实现了 [公式:参见文本] 的根平均平方误差 (RMSE).
- 在无故障条件下达到92.81%的系统输出精度,在最坏的情况下达到67.16%的故障场景.
结论:
- 拟议的数据驱动的LSTM-FTC系统有效地增强了故障期间控制系统的操作.
- 在LSTM-FTC系统的无模型性质提供了相对于传统方法的显著优势.
- 数字双胞胎方法促进了对耐故障控制策略的稳健模拟和验证.
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