首页|基于改进Stanley算法的目标假车路径跟踪控制

基于改进Stanley算法的目标假车路径跟踪控制

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  • 国家科技期刊平台
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为了满足智能汽车封闭场地测试的需求,开发了一种智能车场地测试用软目标车,能够有效地提高场地测试的安全性和效率.在封闭场地功能场景的测试中,软目标车应能够按照预设的GPS轨迹高精度行驶.为了提高目标车的路径跟踪精度,设计了基于偏差的比例、积分、微分和Stanley控制算法的横纵向控制器,基于遗传算法得到Stanley控制算法参数的最优知识库,利用模糊控制算法实现Stanley控制算法参数的自适应调节,基于Carsim和Matlab/Simu-link联合建立了软目标车仿真模型,最后在封闭场地中进行实车验证.结果表明:提出的控制方法能够满足智能汽车封闭场地测试要求.
Path tracking control of soft target vehicle based on improved Stanley algorithm
To meet the requirements of smart car closed field test,a soft target vehicle for smart car field test is developed,which effectively improves the safety and efficiency of field test.In the test of the functional scene of the closed site,the soft target vehicle is able to drive with high precision according to the preset GPS trajectory.To improve the path tracking accuracy of the target vehicle,a horizontal and vertical controller based on deviation proportional,integral,differential and Stanley control algorithm is designed.The optimal knowledge base of Stanley control algorithm parameters is obtained based on genetic algorithm,and the parameters of Stanley control algorithm are accordingly adjusted by fuzzy control algorithm.A soft target vehicle simulation model is built based on Carsim and Matlab/Simulink.Finally,a real vehicle is verified in a closed field.Our results show the proposed control method well meets the requirements of smart car closed field test.

soft target vehicleparticle swarm optimization algorithmgenetic algorithmfuzzy control

李文礼、易帆、封坤、王戡、张智勇

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重庆理工大学 汽车零部件先进制造技术教育部重点实验室,重庆 400054

招商局检测车辆技术研究院有限公司,重庆 401122

软目标车 粒子群优化算法 遗传算法 模糊控制

重庆市自然科学基金面上项目重庆市留学人员回国创业创新支持计划项目重庆市教委科学技术研究项目重庆市技术创新与应用发展专项重大项目

cstc2021jcyjmsxmX0183CX2021070KJQN202201170CSTB2022TIAD-STX0003

2024

10.3969/j.issn.1674-8425(z).2024.02.003

重庆理工大学学报
重庆理工大学

重庆理工大学学报

CSTPCD北大核心
影响因子：0.567
ISSN：1674-8425
年,卷(期)：2024.38(3)
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