CLC number: TP273
On-line Access: 2020-07-10
Received: 2019-04-08
Revision Accepted: 2019-09-16
Crosschecked: 2020-06-03
Cited: 0
Clicked: 5770
Citations: Bibtex RefMan EndNote GB/T7714
Hong-chao Wang, Wei-wei Zhang, Xun-cheng Wu, Hao-tian Cao, Qiao-ming Gao, Su-yun Luo. A double-layered nonlinear model predictive control based control algorithm for local trajectory planning for automated trucks under uncertain road adhesion coefficient conditions[J]. Frontiers of Information Technology & Electronic Engineering,in press.https://doi.org/10.1631/FITEE.1900185 @article{title="A double-layered nonlinear model predictive control based control algorithm for local trajectory planning for automated trucks under uncertain road adhesion coefficient conditions", %0 Journal Article TY - JOUR
不确定路面附着系数条件下一种基于双层非线性模型预测控制的自动驾驶卡车轨迹规划方法1上海工程技术大学机械与汽车工程学院,中国上海市,201620 2湖南大学汽车车身先进设计制造国家重点实验室,中国长沙市,410082 3广西科技大学汽车与交通学院,中国柳州市,545006 摘要:提出一种双层控制算法以规划配备四轮轮毂电机的自动驾驶卡车的行驶轨迹。该控制算法主要由主层非线性模型预测控制(MLN-MPC)算法和次层非线性模型预测控制(SLN-MPC)算法组成,其中,MLN-MPC控制算法用于规划合理的卡车行驶轨迹,SLN-MPC控制算法将车轮纵向滑移率限制在稳定区域,避免卡车在驱动过程中发生过度打滑。总体而言,该控制算法为一个闭环控制系统。在离线仿真环境下,通过AMESim、Simulink、dSPACE和TruckSim仿真软件联合仿真。仿真结果表明,本文所提算法能规划一条合理的车辆避障行驶轨迹,在不确定路面附着系数条件下能将车辆纵向滑移率控制在合理范围。此外,为评估该算法在实际应用中的可行性,在联合仿真系统中加入驾驶员模型验证该算法的稳定性与鲁棒性。与传统的基于PID控制算法相比,该算法具有更低的计算能耗。 关键词组: Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article
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