对滑板车底盘车辆动态状态和静态参数的相互校准估计
Zequn Bei1, Xiang Chen1, Guan Zhou1
1College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, Jiangsu Province, China.
ISA transactions
|December 6, 2025
概括
本研究引入了一种相互校准方法,以提高车辆动态状态估计的准确性,解决非固定底盘合器带来的挑战. 这种新的方法通过校准闭环系统中的动态和静态参数来增强状态估计.
科学领域:
- 车辆动力学和控制控制
- 估计理论 估计理论
- 机器人技术 机器人技术 机器人技术
背景情况:
- 滑板底盘中的非固定合器对准确的车辆动态状态估计提出了挑战.
- 现有的方法与这种系统固有的动态和静态参数不确定性作斗争.
研究的目的:
- 为准确的车辆动态状态估计提出一种新的相互校准估计方法.
- 开发一个闭环系统,校准动态和静态参数.
主要方法:
- 建立了一个非线性7-DOF车辆动态模型.
- 开发了一种校准的忘记因子递归最小方程 (C-FFRLS) 估计器,用于静态参数估计 (质量,CoG,俯冲矩).
- 提出了一个校准的自适应性强大的Cubature Kalman波器 (C-ARCKF) 用于动态状态估计,创建一个闭环的相互校准系统.
主要成果:
- 在C-FFRLS估计器成功估计了车辆的质量,CoG位置,和曲惯性矩.
- 估计的静态参数有效校准了动态模型参数和观察者噪声特征.
- 通过闭环校准,C-ARCKF证明了通过闭环校准准确估计车辆状态.
结论:
- 拟议的相互校准方法显著提高了车辆动态状态估计的准确性.
- 闭环系统有效地解决了非固定底盘合器所带来的挑战.
- 模拟和实验结果验证了拟议方法的有效性.
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