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作 者:郭朝阳 赵远 GUO Zhaoyang;ZHAO Yuan(CCTEG Chinese Institute of Coal Science,Beijing 100000,China;CCTEG Taiyuan Research Institute,Taiyuan 030006,China)
机构地区:[1]煤炭科学研究总院有限公司,北京100000 [2]中国煤炭科工集团太原研究院有限公司,山西太原030006
出 处:《煤矿机电》2023年第3期35-42,共8页Colliery Mechanical & Electrical Technology
摘 要:地下矿用铰接车的路径跟踪控制是铰接车自动驾驶领域中的关键技术,路径跟踪控制方法对于实现高跟踪精度具有重要意义。为了选择性能更优的控制器去控制地下矿用铰接车实现路径跟踪,对已运用在铰接车路径跟踪上的控制方法进行了分类和回顾,主要包括反馈线性化控制、线性二次型最优控制、模型预测控制、纯几何跟踪控制、比例-积分-微分控制、滑动模态控制、智能控制和鲁棒控制。通过比较实例中的控制器性能,得出模型预测控制方法更适用于地下矿用铰接车的路径跟踪控制,且跟踪精度高,具有研究优势。但目前模型预测控制方法大部分以运动学模型和大量简化的动力学模型为预测模型,未广泛在实际控制平台上验证性能,实时性有待优化,这些是未来研究的重点。The path tracking control of underground mining articulated vehicles is a key technology in the field of autonomous driving of articulated vehicles,and the path tracking control method is of great significance for achieving high tracking accuracy.In order to select a controller with better performance to control the underground mining articulated vehicle to achieve path tracking,the control methods that have been applied to the path tracking of the articulated vehicle were classified and reviewed,mainly including feedback linearization control,linear quadratic form optimal control.Model predictive control,pure geometry tracking control,proportional integral differential control,sliding mode control,intelligent control and robust control.By comparing the controller performance in the example,it is concluded that the model predictive control method is more suitable for the path tracking control of underground mining articulated vehicles,and has high tracking accuracy and research advantages.However,most of the current model predictive control methods use kinematics models and a large number of simplified dynamic models as predictive models,which have not been widely used to verify the performance on actual control platforms.Real time performance needs to be optimized,which is the focus of future research.
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