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UKF-based adaptive variable structure observer for vehicle sideslip with dynamic correction

机译:基于UKF的具有动态校正功能的车辆侧滑自适应变结构观察器

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摘要

Knowing vehicle sideslip angle is important and useful in various vehicle active safety applications. However, equipment which could directly measure sideslip angle is usually too expensive for industrial applications, so a reliable, affordable sideslip angle observer is necessary. Model-based observer is affected by the model uncertainty, non-linearity and the road friction inaccuracy. Sensor-based observer might be easily affected by the sensor noise and the bias induced by the road micro-uneven. Thus, an unscented Kalman filter (UKF)-based adaptive variable structural observer with dynamic correction (AUKF) for vehicle body sideslip angle is brought forward in this study. First, an UKF observer with adaptive parameters is used to compensate the model uncertainty. Then, a sensor-based observer is applied to realise a variable structure observer to compensate the estimation error in the highly non-linear region. A pseudointegral method and a zero point reset method are adopted to dynamically correct the bias drift problem in the integral. Both simulations and real vehicle tests validated the proposed approach. The accurate vehicle sideslip angle is measured by a differential global positioning system. Results show that the proposed approach has better performance compared with traditional UKF method, and makes a good foundation for stability control.
机译:知道车辆的侧滑角在各种车辆主动安全应用中是重要且有用的。然而,对于工业应用而言,可以直接测量侧滑角的设备通常过于昂贵,因此需要可靠,负担得起的侧滑角观测器。基于模型的观察者会受到模型不确定性,非线性和道路摩擦误差的影响。基于传感器的观察者可能很容易受到传感器噪声和道路微不平整引起的偏差的影响。因此,本研究提出了基于无味卡尔曼滤波器(UKF)的具有动态校正(AUKF)的车身侧滑角自适应变结构观测器。首先,使用具有自适应参数的UKF观测器来补偿模型不确定性。然后,基于传感器的观察器被应用于实现可变结构的观察器,以补偿高度非线性区域中的估计误差。采用伪积分法和零点复位法动态校正积分中的偏差漂移问题。仿真和实际车辆测试均验证了该方法的有效性。精确的车辆侧滑角由差分全球定位系统测量。结果表明,与传统的UKF方法相比,该方法具有更好的性能,为稳定控制奠定了良好的基础。

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