自动驾驶汽车的无偏移非线性模型预测控制研究  

Offset Free Nonlinear Model Predictive Controller for Autonomous Vehicles

作　　者：刘金波 王超 刘梦可 高原 王宇 王欣志 Liu Jinbo;Wang Chao;Liu Mengke;Gao Yuan;Wang Yu;Wang Xinzhi(Global R&D Center,China FAW Corporation Limited,Changchun 130013;National Key Laboratory of Advanced Vehicle Integration and Control,Changchun 130013)

机构地区：[1]中国第一汽车股份有限公司研发总院,长春130013 [2]高端汽车集成与控制全国重点实验室,长春130013

出　　处：《汽车工程师》2024年第5期20-25,共6页Automotive Engineer

摘　　要：为解决自动驾驶汽车运动控制中基于横向-纵向耦合结构的无偏移非线性模型预测控制(OF-NMPC)的稳态误差问题,使用无迹卡尔曼滤波器观察控制器状态和扰动,并纳入模型预测和参考值计算以消除稳态误差。仿真和实车试验结果表明,所提出的OF-NMPC算法可有效消除稳态误差,提高系统的动态性能。Nonlinear Model Predictive Control(NMPC)method-based motion control has attracted considerable attention in the field of autonomous driving.However,the steady-state error problem has not been comprehensively investigated,especially for nonlinear MPC.This paper seeks to solve the steady-state error problem based on Offset-Free NMPC(OF-NMPC)with a lateral-longitudinal coupling structure.The proposed OF-NMPC uses an Unscented Kalman Filter(UKF)to observe the states and disturbances and incorporates them into the prediction model and reference calculation to eliminate the steady-state error.One of the challenges of OF-NMPC is the need to use optimization methods to obtain reference values,which will obviously increase the considerable computational burden.Based on the appropriate simplification,we get the reference analytical solution without solving nonlinear optimization problems online in real-time.Simulation and real vehicle experiments show that the proposed OF-NMPC can effectively eliminate the steady-state error and improve the system’s dynamic performance.

关 键 词：运动控制 轮胎模型 非线性模型预测控制 路径跟踪 

分 类 号：U461.91[机械工程—车辆工程]