在参数不确定性和外部干扰下,使用适应性增益估计用于地面车辆的强大的动态非线性控制
Cuauhtémoc Acosta Lúa1, Stefano Di Gennaro2, Ariadna Berenice Flores Jiménez3
1Centro Universitario de la Ciénega - Universidad de Guadalajara, Ocotlán, Jalisco, 47820 México; Center of Excellence DEWS - University of L'Aquila, Coppito, 67100 L'Aquila, Italy.
本研究介绍了一种适应性控制策略,用于带有主动前方向 (AFS) 和后扭矩向量 (RTV) 的车辆. 它通过使用先进的滑动模式技术实现了精确的轨迹跟踪和干扰排斥.
科学领域:
- 汽车工程 汽车工程
- 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:
- 控制车辆动态对于安全和性能至关重要.
- 现有的方法与不确定性和外部干扰作斗争.
- 主动前方向 (AFS) 和后扭矩向量 (RTV) 提供了先进的控制功能.
研究的目的:
- 为配备AFS和RTV的车辆开发一个强大的动态非线性控制策略.
- 为了提高在不确定的条件下轨迹跟踪的准确性.
- 为了改善干扰排斥和横向速度估计.
主要方法:
- 实施高阶滑动模式 (HOSM) 估计器,以适应性增益来控制.
- 设计了一种具有适应性增益的新型HOSM观测器,用于横向速度重建.
- 通过使用CarSim软件进行数值模拟验证.
主要成果:
- 尽管参数不确定性,但拟议的控制器证明了准确的轨迹跟踪.
- 在双车道换车机动过程中观察到优异的短暂行为和干扰排斥.
- 适应性HOSM观察器在动态条件下有效地重建了横向速度.
结论:
- 适应性HOSM控制策略为具有AFS和RTV的车辆的轨迹跟踪提供了强大的解决方案.
- 集成观察器在动态驾驶场景中提高了性能.
- 这种方法在具有挑战性的机动中明显优于传统方法.
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