适应性神经故障耐受跟踪控制器用于受到多次功率漂移故障影响的状态受约束系统
Yadong Yang1, Xuan Qiu2, Qikun Shen1
1College of Information Engineering, Yangzhou University, Yangzhou 225127, China.
ISA transactions
|April 16, 2025
概括
本研究引入了自适应神经故障耐受性控制 (FTC) 来管理新的传感器和执行器故障,包括功率漂移. 开发的算法确保了系统稳定性和约束满足,尽管存在不确定性.
科学领域:
- 控制工程 控制工程 控制工程
- 人工智能的人工智能
- 系统动力学系统动力学
背景情况:
- 受到国家限制的系统容易受到各种传感器和执行器故障的影响.
- 新出现的故障,例如传感器和执行器的功率漂移,对系统稳定性构成重大挑战.
- 现有的耐故障控制 (FTC) 方法可能无法充分解决这些新型故障类型.
研究的目的:
- 对状态受约束系统的自适应神经故障耐受性控制 (FTC) 进行调查.
- 解决新的传感器和执行器故障,包括动力漂移故障.
- 制定一个强大的控制策略,保持系统稳定性,并遵守约束.
主要方法:
- 开发一种使用辅助信号来弥补多个功率漂移故障的新型控制器.
- 辐射基函数神经网络 (RBFNNs) 的应用,以近似不确定函数并减少计算负载.
- 将后退方法与障碍Lyapunov函数集成,以设计自适应FTC算法.
主要成果:
- 所有系统信号都被证明保持半全球界限.
- 控制错误有效地被驱动到接近零的小范围.
- 系统约束在没有违反的情况下始终保持.
结论:
- 开发的自适应FTC算法对于具有新型故障的状态受约束系统是有效和可行的.
- 建议的控制策略有效地弥补了传感器和执行器的功率漂移故障.
- 该方法确保了系统的稳定性和遵守操作约束.
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