在执行器和传感器故障的情况下,用于四旋翼的容错控制
Kenji Fabiano Ávila Okada1, Aniel Silva Morais1, Laura Ribeiro1
1Faculty of Electrical Engineering, Federal University of Uberlândia, Uberlândia 38408-100, Brazil.
Sensors (Basel, Switzerland)
|November 27, 2024
概括
这项研究提高了使用故障检测和诊断 (FDD) 与卡尔曼波器 (KF) 变异用于故障耐受性控制 (FTC) 的四旋翼安全性. 适应性FDD方法显著提高了对传感器和执行器故障的稳定性和可靠性.
科学领域:
- 航空航天工程 航空航天工程
- 控制系统 控制系统
- 机器人技术 机器人技术 机器人技术
背景情况:
- 无人驾驶飞行器 (UAV),特别是四旋翼飞机,由于复杂的动力学和环境因素,面临来自传感器和执行器故障的操作风险.
- 确保无人机操作的安全性,可靠性和成本效益需要强大的故障检测和诊断 (FDD) 和容错控制 (FTC) 策略.
研究的目的:
- 实施和评估不同基于卡尔曼波器 (KF) 的FDD方法,用于四旋翼飞机的故障估计.
- 为了实现有效的故障耐受性控制 (FTC) 的四旋翼经历非线性执行器和传感器故障,包括同时发生.
主要方法:
- 实施三种KF变体:线性KF,扩展KF (EKF) 和无气味KF (UKF).
- 包括KF的三级和自适应变异来增强故障估计.
- 将FDD方法集成到FTC架构中,用于四旋翼稳定.
主要成果:
- 基于KF的自适应FDD方法在复杂场景中显示出优异的故障估计性能.
- 尽管传感器和执行器有故障,但FTC架构成功地保持了四旋翼的稳定性.
- 通过拟议的FDD/FTC系统,四旋翼飞机的安全性和可靠性得到了显著改善.
结论:
- 基于卡尔曼波器的FDD方法,特别是自适应变体,对于提高四旋翼机故障耐受性是有效的.
- 开发的FTC系统为在故障条件下保持稳定的无人机运行提供了强大的解决方案.
- 这项研究有助于开发更安全,更可靠的自动驾驶飞行器系统.
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