基于自适应多尺度超螺旋算法的无人机集群姿态同步控制

蔡运颂; 许璟; 牛玉刚

doi:10.16383/j.aas.c220759

基于自适应多尺度超螺旋算法的无人机集群姿态同步控制

doi: 10.16383/j.aas.c220759

蔡运颂^{1, 2,},
许璟^{1, 2,},
牛玉刚^{1, 2,}

1.
华东理工大学信息科学与工程学院上海 200237
2.
华东理工大学能源化工过程智能制造教育部重点实验室上海 200237

基金项目: 国家自然科学基金(62173141, 62073139), 上海市自然科学基金(22ZR1417900)资助

详细信息

作者简介:
蔡运颂：华东理工大学信息科学与工程学院硕士研究生. 主要研究方向为滑模控制, 多智能体和无人机控制. E-mail: y30210956@mail.ecust.edu.cn

许璟：华东理工大学信息科学与工程学院副教授. 主要研究方向为高阶滑模观测与控制, 无人机系统建模与控制, 智能优化算法和人工智能技术. 本文通信作者.E-mail: jingxu@ecust.edu.cn

牛玉刚：华东理工大学信息科学与工程学院教授. 主要研究方向为随机控制系统, 滑模控制, 无线传感网络和微电网能量管理. E-mail: acniuyg@ecust.edu.cn

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出版历程
- 收稿日期: 2022-09-22
- 录用日期: 2023-02-12
- 网络出版日期: 2023-03-15
- 刊出日期: 2023-08-21

Attitude Consensus Control of UAV Swarm Based on Adaptive Multi-scale Super-twisting Algorithm

CAI Yun-Song^{1, 2
,},
XU Jing^{1, 2
,},
NIU Yu-Gang^{1, 2
,}

1.
College of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237
2.
Key Laboratory of Intelligent Manufacturing of Energy and Chemical Processes of Ministry of Education, East China University of Science and Technology, Shanghai 200237

Funds: Supported by National Natural Science Foundation of China (62173141, 62073139) and the Natural Science Foundation of Shanghai (22ZR1417900)

More Information

Author Bio:
CAI Yun-Song　Master student at the College of Information Science and Engineering, East China University of Science and Technology. His research interest covers sliding mode control, multi-agent, and UAV control

XU Jing　Associate professor at the College of Information Science and Engineering, East China University of Science and Technology. Her research interest covers high-order sliding mode observation and control, UAV system modeling and control, intelligent arithmetic optimization, and artificial intelligence technology. Corresponding author of this paper

NIU Yu-Gang　Professor at the College of Information Science and Engineering, East China University of Science and Technology. His research interest covers stochastic control system, sliding mode control, wireless sensor network, and microgrid energy management

摘要

摘要: 四旋翼无人机(Unmanned aerial vehicle, UAV)系统姿态角和角速度分别为运行在不同时间尺度上的慢、快动态. 由于输入扰动的上界难以精确估计, 本文提出一种基于自适应多尺度超螺旋(Super-twisting, STW)滑模算法的无人机集群一致性控制策略. 首先, 建立无人机集群系统的姿态角模型, 并通过奇异摄动理论将其化为两时间尺度形式. 基于系统的快慢特性, 本文设计两时间尺度的超螺旋滑模算法, 并采用自适应增益处理无人机集群系统的未知边界非线性. 此外, 还提出一种改进型自适应多尺度超螺旋滑模算法, 进一步减少系统的一致性收敛时间, 实现无人机集群姿态角有限时间内同步. 最后通过仿真分析, 验证两种自适应多尺度超螺旋算法的正确性和有效性.
- 奇异摄动 /
- 超螺旋算法 /
- 多尺度 /
- 姿态协同 /
- 四旋翼无人机
Abstract: In a UAV (unmanned aerial vehicle) system, the attitude angle and angular velocity of the UAV are, respectively, the slow and fast dynamics operating in different time scales. Due to the difficulty in the estimation of the bound of disturbance, this paper proposes a control method for UAV swarm, based on the adaptive multi-scale STW (super-twisting) sliding mode algorithm. First, the attitude model of the UAV swarm system is established, which is transformed into a two-time-scale model via singular perturbation theory. On this basis, this paper designs a two-time-scale STW sliding mode algorithm with adaptive gains to deal with the perturbations and unknows. Furthermore, by adding a few linear iterms, a modified adaptive STW control algorithm is also provided, which further reduces the convergence time and achieves the synchronization of the attitudes in finite time. Finally, the effectiveness of two different adaptive multi-scale STW algorithms are verified through simulations.
- Singular perturbation /
- STW /
- multi-scale /
- attitude coordination /
- quadrotors

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图 1 四旋翼无人机多智能体

Fig. 1 The multi-agent of quadrotors

下载: 全尺寸图片幻灯片

图 2 自适应多尺度STW算法控制下的无人机姿态历时曲线

Fig. 2 Trajectories of attitudes under the adaptive multi-scale STW controller

下载: 全尺寸图片幻灯片

图 3 改进型自适应多尺度STW算法控制下的无人机姿态历时曲线

Fig. 3 Trajectories of attitudes under the modified adaptive multi-scale STW controller

下载: 全尺寸图片幻灯片

表 1 四旋翼无人机姿态角系统性能指标

Table 1 Performance index of a quadrotor＇s attitude system

平均收敛时间(s) 平均稳态误差(rad)

STW滑模算法 2.587 1.76×10⁻⁷
改进型STW滑模算法 1.947 3.56×10⁻⁷
文献[30]中的算法 10.870 4.24×10⁻⁶

下载: 导出CSV

参考文献(30)

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基于自适应多尺度超螺旋算法的无人机集群姿态同步控制

doi: 10.16383/j.aas.c220759

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Attitude Consensus Control of UAV Swarm Based on Adaptive Multi-scale Super-twisting Algorithm

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目录

	平均收敛时间(s)	平均稳态误差(rad)
STW滑模算法	2.587	1.76×10⁻⁷
改进型STW滑模算法	1.947	3.56×10⁻⁷
文献[30]中的算法	10.870	4.24×10⁻⁶

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基于自适应多尺度超螺旋算法的无人机集群姿态同步控制

doi: 10.16383/j.aas.c220759

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出版历程

Attitude Consensus Control of UAV Swarm Based on Adaptive Multi-scale Super-twisting Algorithm

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