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车辆轨迹模型预测控制器的算法研究

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为提高无人驾驶汽车行驶控制中的跟踪精度和车辆稳定性,提出了一个改进的模型预测控制器(MPC).首先,为解决高速转弯工况下轮胎侧偏刚度的强非线性特性导致的车辆失稳问题,建立了轮胎动态侧偏刚度估计器进行实时估计;在此基础上,利用改进粒子群算法对现有模型预测控制器的时域参数进行优化,以提高算法跟踪精度和稳定性;最后,为验证控制器的效果,选取合适的工况进行了联合仿真测试.结果表明,改进控制器在高速转弯的工况下,跟踪精度误差降为4.9%,横摆角误差降为2.6%,比传统模型预测控制器分别提高了67.8%和62.3%,比模糊控制算法优化的控制器分别提高了55.8%和58%.
Research on Algorithm of Vehicle Trajectory Model Predictive Controller
An improved model predictive controller(MPC)was proposed to improve the tracking accu-racy and vehicle stability of driverless vehicles.Firstly,in order to solve the vehicle instability problem caused by the strong nonlinear characteristics of tire side stiffness under high-speed turning conditions,a tire dynamic side stiffness estimator was established for real-time estimation.On this basis,the improved particle swarm optimization algorithm was used to optimize the time domain parameters of the existing model prediction controller to improve the tracking accuracy and stability of the algorithm.Finally,in order to verify the effect of the controller,the appropriate working conditions were selected for co-simula-tion test.The results show that the tracking accuracy error and yaw Angle error of the improved control-ler are reduced to 4.9%and 2.6%respectively under the condition of high-speed turning,which are 67.8%and 62.3%higher than those of the traditional model forecast controller,and 55.8%and 58%higher than those of the controller optimized by fuzzy control algorithm.

driverless vehiclestrajectory trackingestimation of lateral stiffnessimproved model predic-tive controllerparticle swarm optimization algorithm

候峙朴、范英、赵敏、代晓文、许晋军、李一帆

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太原科技大学 车辆与交通工程学院,山西 太原 030024

无人驾驶车辆 轨迹跟踪 侧偏刚度估计 改进的模型预测控制器 粒子群算法

山西省科学技术发展计划项目山西省大创项目山西省研究生教改项目山西省研究生创新项目

201903D121176S202296832022YJJG2082022Y704

2024

10.3969/j.issn.1673-3193.2024.03.011

中北大学学报(自然科学版)
中北大学

中北大学学报(自然科学版)

影响因子：0.258
ISSN：1673-3193
年,卷(期)：2024.45(3)