基于方位信息的轮式机器人动态编队控制
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作者单位:

1.陕西科技大学,电气与控制工程学院,西安710021;2.陕西科技大学,机电工程学院,西安710021

作者简介:

李 艳(1972—),女,教授,主要从事工业自动化、机器人轨迹跟踪、多机编队等方向研究。

通讯作者:

贺彬彬(1999—),女,(Email)1798759270@qq.com。

中图分类号:

TP242

基金项目:

陕西省重点研发计划项目(2023-YBGY-277,2023-YBGY-409)。


Dynamic formation control of wheeled robots based on azimuth information
Author:
Affiliation:

1.School of Electrical and Control Engineering, Shaanxi University of Science & Technology, Xi’an 710021, P. R. China;2.School of Mechanical and Electrical Engineering, Shaanxi University of Science & Technology, Xi’an 710021, P. R. China

Fund Project:

Supported by Key Research and Development Program of Shaanxi Province(2023-YBGY-277,2023-YBGY-409).

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    摘要:

    针对非完整约束的多机器人动态编队中,各机器人只能获取相邻机器人方位信息的情况,提出一种纯方位角信息的分布式PID(proportion integration derivative)编队控制算法。考虑领航机器人易受风向或路面平整度等扰动影响,带来无法保持编队队形的问题,算法通过引入跟随机器人的相对位置和相对速度反馈,有效消除稳态误差,抑制干扰的影响,改善系统的动态性能,保证系统的全局稳定性。然后,利用Routh-Hurwitz稳定性判据进行分析,验证编队系统的全局稳定性。最后,通过仿真实验比较所提控制律与基于纯比例和比例积分的控制律在收敛速度、抗干扰能力等方面的性能。仿真结果表明:所提控制律使领航者受到干扰后依然形成期望编队,实现对领航者轨迹的快速跟踪,总方位角误差的相对最大偏差下降了5.4%。

    Abstract:

    Addressing the scenario in which each robot can only acquire the azimuth information of adjacent robots in dynamic formations with incomplete constraints, this paper proposes a distributed PID formation control algorithm based solely on azimuth information. With considering that the pilot robot is susceptible to disturbances such as wind direction or road surface irregularities, which may disrupt formation maintenance, the algorithm introduces relative position and velocity feedback of the follower robots. This approach effectively eliminates steady-state error, suppresses the influence of disturbances, improves system dynamic performance, and ensures global system stability. Then, the Routh-Hurwitz stability criterion is used for stability analysis, verifying the global stability of the formation system. Finally, simulation experiments compare the performance of the proposed control law with control laws based on pure proportional and proportional-integral strategies in terms of convergence speed and disturbance rejection. The results show that the proposed control law enables the formation to recover after disturbances and achieve rapid trajectory tracking of the leader, with the relative maximum deviation of the total azimuth error reduced by 5.4%.

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李艳,贺彬彬,李明辉,戴庆瑜.基于方位信息的轮式机器人动态编队控制[J].重庆大学学报,2025,48(4):84-96.

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  • 收稿日期:2023-07-22
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  • 在线发布日期: 2025-04-25
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