多源干扰下的智能车模型预测纵向运动抗干扰控制  

Model Predictive Anti-disturbance Control for Longitudinal Motion of Intelligent Vehicles Under Multi-source Disturbances

作　　者：张忠[1,2] 吴晓建 江会华 张超 万宇康[2] Zhang Zhong;Wu Xiaojian;Jiang Huihua;Zhang Chao;Wan Yukang(School of Advanced Manufacturing,Nanchang University,Nanchang 330031;Jiangling Motors Co.,Ltd.,Nanchang 330052)

机构地区：[1]南昌大学先进制造学院,南昌330031 [2]江铃汽车股份有限公司,南昌330052

出　　处：《汽车工程》2024年第10期1816-1828,1919,共14页Automotive Engineering

基　　金：国家自然科学基金(52262054,52202466,52062036);江西省研究生创新专项资金(YC2023-S158)资助。

摘　　要：智能车纵向运动控制面临模型失配和外部环境变化等多源干扰,影响速度跟踪的精确性,本文针对性提出一种结合扰动观测和模型预测控制(model predict control,MPC)算法的纵向运动抗干扰控制方法。首先,根据车辆纵向动力学模型分析车辆纵向加速度与各项作用力之间的关系,然后将其简化为含多源干扰的质点运动型并设计模型预测控制器作为上层控制器。其次,针对内部未建模动态干扰及外部随机干扰,设计线性扩张状态观测器(linear extended state observe,LESO)进行实时估计,并通过前馈环节实施补偿,且分析了MPC闭环稳定性和LESO收敛性,最终形成扰动补偿和状态反馈的模型预测最优调节控制律。进一步地,为确保控制策略的高效执行,提出1阶自抗扰控制器作为下层控制器,将期望加速度转换为发动机转矩,从而实现对车速的闭环控制。最后,将算法部署在车载微控制单元(microcontroller unit,MCU)上,在多个速度和道路工况下进行实车测试。实验结果表明,所提出的策略可以快速且精确跟踪目标车速,具备良好的抗干扰能力。The precision of speed tracking in the longitudinal motion control of intelligent vehicles is affected by multiple sources of disturbances,such as model mismatch and changes in external environments.In this paper,a longitudinal motion anti-disturbance control method that combines disturbance observation and Model Predictive Control(MPC)algorithm is accordingly proposed.Firstly,the relationship between the longitudinal acceleration of the vehicle and various forces is analyzed according to the longitudinal dynamics model of the vehicle,and then it is simplified into a particle motion model with multiple sources of disturbance and a model predictive controller is designed as the upper controller.Secondly,for the internal unmodeled dynamic disturbances and external random disturbances,a linear extended state observer(LESO)is designed to perform real-time estimation and compensation is implemented through a feedforward loop.The closed-loop stability of MPC and the convergence of LESO are analyzed,and finally a model predictive optimal regulation control law of disturbance compensation and state feedback is formed.Furthermore,in order to ensure efficient execution of the control strategy,a first-order anti-disturbance controller is proposed as the lower controller to convert the desired acceleration into engine torque,thereby realizing closed-loop control of the vehicle speed.Finally,the algorithm is deployed on a in-vehicle Microcontroller Unit(MCU)and tested on a real vehicle under multi-speeds and road conditions.The results show that the proposed strategy can quickly and accurately track the target vehicle speed,with excellent anti-disturbance ability.

关 键 词：智能汽车 纵向速度跟踪 抗干扰控制 模型预测控制 扩张状态观测器 

分 类 号：U463.6[机械工程—车辆工程] TP273[交通运输工程—载运工具运用工程]