对于实时车辆状态估计和改善道路安全的TS模糊方法
Mohamed Saber1, Mohamed Ouahi2, Saad Motahhir3
1Laboratory of Applied Sciences and Emerging Technologies, National School of Applied Sciences, BP 72, My Abdallah Avenue Km. 5 Imouzzer Road, Fez, Morocco. mohamed.saber1@usmba.ac.ma.
Scientific reports
|October 8, 2025
概括
这项研究引入了一种新的Takagi-Sugeno (T-S) 模糊观察器,用于实时估计车辆动态和道路状况. 通过提高驾驶辅助系统的准确性和计算效率,先进的观察器提高了汽车安全性.
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:
- 安全驾驶需要准确估计车辆动态和道路特性.
- 目前的方法,如比例多元积分观察器 (PMIO) 和模糊未知输入观察器 (FUIO),在实时应用方面存在局限性.
- 先进的驾驶辅助系统 (ADAS) 需要强大而高效的状态估计.
研究的目的:
- 开发一个计算效率高和强大的Takagi-Sugeno (T-S) 模糊功能观察器.
- 为了实时估计未测量的车辆状态 (侧滑角度,曲率,角位移) 和道路曲率.
- 克服嵌入式汽车系统现有观察员的局限性.
主要方法:
- 在观察者设计中利用了利亚普诺夫-克拉索夫斯基稳定理论.
- 用线性矩阵不等式 (LMI) 来进行参数优化.
- 开发了一个Takagi-Sugeno (T-S) 模糊的功能观察者架构.
主要成果:
- 拟议的TS模糊观察员与全序观察员 (FO),PMIO和FUIO相比,表现出更高的准确性和更快的趋同.
- 实现显著降低计算成本,确保实时可行性.
- 循环中的处理器 (PIL) 验证证实了其实际适用性.
结论:
- 新的TS模糊功能观察器为实时车辆状态估计提供了计算效率高和强大的解决方案.
- 它的性能优势使其适合集成到ADAS中,以提高驾驶安全.
- 该研究证实了观察员的新性和减少事故风险的实际潜力.
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