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智能车车速最优控制策略与算法研究
供稿: 张丽;徐海钦;王子文;王福忠;张涛 时间: 2020-09-10 次数:

张丽, 徐海钦, 王子文,.智能车车速最优控制策略与算法研究[J].河南理工大学学报(自然科学版),2020,39(5):94-100.

ZHANG L, XU H Q, WANG Z W, et al.Study on the optimal speed control strategy and algorithm for intelligent vehicle[J].Journal of Henan Polytechnic University(Natural Science) ,2020,39(5):94-100.

智能车车速最优控制策略与算法研究

张丽, 徐海钦, 王子文, 王福忠, 张涛

河南理工大学 电气工程与自动化学院,河南 焦作454000

摘要:在全国大学生智能车竞赛中,光电四轮组的单车竞速项目取得优异成绩的关键就是最大限度地提高车速,但是由于赛道元素的多元化(如增加圆环、环岛和十字回环等),简单的赛道图像处理和传统的PID控制算法已不能很好地控制智能车在最短的时间内实现加速与减速。本文提出一种图像与速度关联的串级控制方式,首先利用逆透视变换对赛道图像做优化处理 然后对优化后的赛道图像进行中心推算,并将速度环与转向环构成串级控制,最后由人工蜂群算法实时整定控制系统的PID参数,在最短时间内将车速调节至动态的设定值,使车速时刻动态保持最优状态。试验结果表明,该算法不仅提高了智能车的车速和车速控制的稳定性,而且增强了智能车对光照环境的适应能力。

关键词:智能车;车速控制;人工蜂群算法;PID控制;逆透视变换

doi:10.16186/j.cnki.1673-9787.2020.5.14

基金项目:国家自然科学基金资助项目(U1804143 );河南省开放实验室研究项目(KG2016-7 );河南省高等学校重点科研项目 18A470014);河南理工大学博士基金资助项目(B2017-20

收稿日期:2019/12/15

修回日期:2020/02/28

出版日期:2020/09/15

Study on the optimal speed control strategy and algorithm for intelligent vehicle

ZHANG Li, XU Haiqin, WANG Ziwen, WANG Fuzhong, ZHANG Tao

School of Electrical Engineering and Automation Henan Polytechnic University Jiaozuo 454000 HenanChina

Abstract:In the national college student smart car competitionthe key to achieve excellent results in the photoelectric four-wheel cycle racing project is to maximize the speedyet because of many diversified track elements such as ringsloop islands and other elementssimple track image processing and traditional PID control algorithm can not enable the smart car to accelerate and decelerate in the shortest possible time. The cascade control method related to image and velocity proposed in the papercould realize process optimization and center calculation of the track image through reverse perspective transformationand could achieve cascade control on speed loop and steering loop. By artificial bee colony algorithm imposing real-time tuning control on PID parametersthe velocity of the vehicle could be maintain in its best state.Experimental results showed that the algorithm could not only improve the speed and speed control stability of intelligent vehiclebut also enhance the adaptability of intelligent vehicle to light environment.

Key words:intelligent vehicle;speed control;artificial bee colony algorithm;PID control;reverse perspective transtormation

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