在传感器故障下,电动汽车侧面动态的多通道量子化输出反故障耐受性跟踪控制
Ting-Ting Pan1, Xiao-Heng Chang1
1School of Artificial Intelligence and Automation, Wuhan University of Science and Technology, Wuhan, Hubei, 430081, China.
ISA transactions
|November 20, 2025
概括
本研究涉及电动汽车 (EV) 侧面控制与传感器故障使用模糊观察员和弹性控制器. 拟议的方法确保了强大的跟踪性能,尽管存在不确定性和故障.
科学领域:
- 控制系统工程 控制系统工程
- 汽车工程 汽车工程
- 模糊逻辑系统 模糊逻辑系统
背景情况:
- 电动汽车 (EV) 需要精确的横向动力控制,以确保安全性和性能.
- 传感器故障和数据量化可以显著降低控制系统的可靠性.
- 车辆参数 (速度,质量,惯性) 的非线性变化使控制设计复杂化.
研究的目的:
- 为了研究EV横向动态的多通道量子化输出反跟踪控制.
- 为应对传感器故障和参数不确定性带来的挑战.
- 为了确保强大的跟踪性能和控制输出稳定性.
主要方法:
- 将EV横向动力学建模为具有规范局限不确定性的Takagi-Sugeno (T-S) 模糊模型.
- 设计一个非脆弱的模糊观察者来处理添加式随机传感器故障.
- 开发一个弹性控制器,以实现H∞跟踪和L2-L∞性能.
主要成果:
- 设计的观察器和控制器有效地弥补传感器故障和参数变化.
- 该系统实现了对跟踪错误的保证H∞跟踪性能.
- 控制输出满足L2-L∞性能标准,确保稳定性.
结论:
- 拟议的非脆弱的模糊观察器和弹性控制器为强大的EV横向控制提供了有效的解决方案.
- 该方法通过在各种具有挑战性的道路条件下进行共模拟来验证.
- 这种方法提高了电动汽车自动驾驶系统的安全性和可靠性.
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