摘要
为了增强车辆在外界干扰存下的路径跟随性能,提出了一种基于广义预测控制(GPC)的主动转向控制器来保证车辆对于路径的跟踪能力.采用受控自回归积分滑动平均模型(CARIMA)作为预测模型,通过带遗忘因子的最小二乘法辨识方法获得CARIMA模型参数,避免了由于车辆非线性造成的参数化建模不准确、繁琐问题.使用车辆路径侧向跟踪误差作为控制器输入,方向盘附加转角作为输出,与驾驶员方向盘转角进行综合,获得车辆方向盘最终转角.在Simulink-CarSim联合仿真环境下,验证了所设计控制器在双移线工况有强侧向风干扰时车辆对路径的跟随性能.
In order to improve the lane tracking capability of vehicles under disturbances, an active steering system based on generalized predictive controller was proposed, of which a controlled auto-regressive inte- grated moving-average model （CARIMA） was used as the inner model. Considering the complexity and uncertainty of vehicle parametric modeling process, a recursive least square method was applied to estimate the parameters in the CARIMA model. The controller used the deviation between the vehicle lateral posi- tion and desired lateral positon as the input and steering wheel angle as the output. Based on driver steer- ing wheel input, the final corrected steering wheel angle was obtained. The performances of the controller were examined in the Simulink-CarSim environment under strong lateral wind condition in standard double- lane-change operating experiment.
出处
《上海交通大学学报》
EI
CAS
CSCD
北大核心
2016年第3期401-406,共6页
Journal of Shanghai Jiaotong University
基金
国家自然科学基金(51375299)
机械系统与振动国家重点实验室课题(MSV201505)资助项目
关键词
主动转向
车道保持
路径跟随
广义预测控制
active steering
lane keeping
path following
generalized predictive control
