网络化Euler-Lagrange系统的分布式编队机动控制

杨吉康; 于晋伟; 杨卫华

doi:10.21656/1000-0887.430130

网络化Euler-Lagrange系统的分布式编队机动控制

doi: 10.21656/1000-0887.430130

太原理工大学数学学院，太原 030600

基金项目:

山西省自然科学基金项目 20210302124546

详细信息

作者简介:
杨吉康(1997—)，男，硕士生(E-mail: athosm1z@163.com)

杨卫华(1984—)，男，教授，博士，博士生导师

通讯作者:
于晋伟(1989—)，男，讲师，博士(通讯作者. E-mail: tyut_math_y@163.com)

中图分类号: TP273⁺.2
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- 文章访问数: 427
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- 被引次数: 0
出版历程
- 收稿日期: 2022-04-27
- 修回日期: 2023-06-11
- 刊出日期: 2023-07-01

Distributed Formation Maneuver Control of Networked Euler-Lagrange Systems

School of Mathematics, Taiyuan University of Technology, Taiyuan 030600, P.R.China

摘要

摘要: 研究了网络化Euler-Lagrange系统自适应编队机动控制问题.针对参数不确定的Euler-Lagrange系统, 利用滑模控制方法提出了一种自适应编队机动控制算法.基于Lyapunov稳定性理论, 证明了闭环系统的稳定性.该算法的显著特点是通过引入一种特殊的有向网络拓扑来描述智能体之间的通信交互行为, 使得系统中跟随者在不需要知道或估计时变机动参数的情况下, 能够实现编队的方向、平移、形状的连续改变.最后对提出的自适应编队机动控制算法进行数值模拟以验证该控制方案的有效性.
- 编队机动控制 /
- 分布式控制 /
- 网络化Euler-Lagrange系统 /
- 滑模控制
Abstract: The adaptive formation maneuver control of networked Euler-Lagrange systems was studied. By means of the sliding mode control approach, an adaptive formation maneuver control algorithm was proposed. Based on the Lyapunov stability theory, the stability of the closed-loop system was proved. The remarkable feature of the algorithm is the special directed network topology introduced to describe the communication interaction behavior between agents. Hence, without the need for knowing or estimating the time-varying maneuver parameters only known to the leaders, the followers in the system can realize the changes of formation continuously, including the scale, the direction, the displacement and the shape. Numerical simulation results verify the effectiveness of the proposed control scheme.
- formation maneuver control /
- distributed control /
- networked Euler-Lagrange system /
- sliding mode control

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图 1 标称队形

Figure 1. The nominal formation

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图 2 通信图

Figure 2. The communication diagram

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图 3 不同时刻系统的运动状态

Figure 3. Motion states of the 7 agents at different moments

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图 4 系统的追踪位置误差

注为了解释图中的颜色，读者可以参考本文的电子网页版本，后同.

Figure 4. Tracking position errors of the system

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图 5 系统的追踪速度误差

Figure 5. Tracking velocity errors of the system

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图 6 不同时刻系统的控制器状态

Figure 6. Controller states of the 7 agents at different moments

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图 7 系统的自适应参数状态

Figure 7. Adaptive parameter states of the 7 agents at different moments

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