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Tracking of Vehicle Motion on Highways and Urban Roads Using a Nonlinear Observer

机译:使用非线性观测器跟踪高速公路和城市道路上的车辆运动

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This paper focuses on the development and use of a nonlinear observer for tracking of vehicle motion trajectories while using a radar sensor. Previous results on vehicle tracking have typically used an interacting multiple model filter that needs different models for different modes of vehicle motion. This paper uses a single nonlinear vehicle model that can be used for all modes of vehicle motion. Previous nonlinear observer design results from the literature do not work for the nonlinear system under consideration due to the wide range of operating conditions that need to be accommodated. Hence, a new nonlinear observer design technique that utilizes better bounds on the coupled nonlinear functions in the dynamics is developed. The exponential stability of the observer is established using Lyapunov techniques. The observer design with the developed technique is then implemented in both simulations and experiments. Experimental results show that the observer can simultaneously and accurately estimate longitudinal position, lateral position, and velocity and orientation variables for the vehicle from radar measurements. Results are presented both for tracking of vehicle maneuvers on highways and of maneuvers on urban roads at traffic intersections where turns and significant changes in vehicle orientation can occur.
机译:本文着重研究开发和使用非线性观测器跟踪使用雷达传感器的车辆运动轨迹。车辆跟踪的先前结果通常使用交互的多模型过滤器,该过滤器需要针对不同的车辆运动模式使用不同的模型。本文使用单个非线性车辆模型,该模型可用于所有车辆运动模式。由于需要适应多种工作条件,因此先前文献中的非线性观测器设计结果不适用于所考虑的非线性系统。因此,开发了一种新的非线性观测器设计技术,该技术在动力学中利用了耦合非线性函数的更好界限。观测者的指数稳定性是使用Lyapunov技术建立的。然后,在模拟和实验中都采用了具有发达技术的观察者设计。实验结果表明,观察者可以通过雷达测量同时准确地估计车辆的纵向位置,横向位置以及速度和方向变量。给出的结果既可用于跟踪高速公路上的车辆操纵,也可以用于在交通交叉路口处发生弯道和车辆方向发生重大变化的城市道路上的操纵。

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