基于μ综合的无人驾驶车辆路径跟随串级鲁棒控制方法  

UGV Robust Path Following Control under Double Loop Structure with μ Synthesis

作　　者：宋彦[1] 赵盼[1] 陶翔[1] 李碧春[1] 梁华为[1] 梅涛[1] 

机构地区：[1]中国科学院合肥物质科学研究院先进制造技术研究所,安徽合肥230088

出　　处：《机器人》2013年第4期417-424,共8页Robot

基　　金：国家自然科学基金重点资助项目(91120307);国家自然科学基金青年基金资助项目(50908222)

摘　　要：无人驾驶车辆做横向机动过程中,会发生由模型不确定性引发的路径跟随性能下降,为解决这一问题,设计了以横摆稳定控制作为内环、路径跟随控制作为外环的串级控制结构.提出了基于μ综合的横摆稳定控制方法.仿真表明,在模型参数发生变化时,对比H∞和PID控制,μ综合方法的控制效果受模型不确定性影响最小.在对比实验中,该方法的均方根误差比PID控制降低了1/3,证明该方法能够在车辆模型参数变化时保证控制系统的鲁棒稳定性与鲁棒性能.For the problem that the path following performance is degraded due to model uncertainty of the unmanned ground vehicle（UGV） during lateral maneuvering,a double loop control structure is designed,in which the path following control is the external loop and the yaw stability control is the inner loop respectively.A robust yaw stability control based on μ synthesis is proposed.Simulation results show that the UGV based on this method has better performance than PID（proportional-integral-derivative） and H∞ controller when model parameters are changed.In comparison experiments,the root mean square error of this method is 1/3 less than PID.The result shows that this method also has robust stability and robust performance with respect to uncertain vehicle parameters.

关 键 词：无人驾驶车辆 路径跟随 Μ综合 鲁棒稳定性 鲁棒性能 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置]