系统仿真学报 ›› 2022, Vol. 34 ›› Issue (5): 978-993.doi: 10.16182/j.issn1004731x.joss.20-0980

• 仿真建模理论与方法 • 上一篇    下一篇

基于改进势场的无人机编队恢复与一致性仿真

王宁(), 代冀阳(), 应进   

  1. 南昌航空大学信息工程学院,江西  南昌  330063
  • 收稿日期:2020-12-07 修回日期:2021-02-06 出版日期:2022-05-18 发布日期:2022-05-25
  • 通讯作者: 代冀阳 E-mail:15979103963@163.com;djiyang@163.com
  • 作者简介:王宁(1994-),男,硕士,研究方向为无人机协同控制,智能控制技术。E-mail:15979103963@163.com
  • 基金资助:
    国家自然科学基金(61663032)

UAV Formation Recovery and Consistency Simulation Based on Improved Potential Field

Ning Wang(), Jiyang Dai(), Jin Ying   

  1. School of Information Engineering, Nanchang Hang Kong University, Nanchang 330063, China
  • Received:2020-12-07 Revised:2021-02-06 Online:2022-05-18 Published:2022-05-25
  • Contact: Jiyang Dai E-mail:15979103963@163.com;djiyang@163.com

摘要:

针对多无人机编队防撞、编队恢复及位置和速度收敛一致性问题,提出以改进势场原理与一致性理论为基础的分布式协同编队控制算法。建立静态障碍物模型、无人机质点模型与二阶系统动态模型;定义含协调因子和通信权重的机间协调势场函数,实现防撞和队形恢复的控制目标;在基本一致性协议中引入编队中心参考向量、期望速度和速度镇定项,实现位置和速度的收敛一致性;结合改进的一致性协议与改进势场作用下的合加速度设计协同编队控制算法,并由Hamilton函数证明该算法的稳定收敛性。仿真结果表明:该方法可以实现防撞、队形恢复及位置与速度收敛一致的控制目标。

关键词: 协同编队, 协调势场函数, 通信权重, 编队恢复, 一致性算法

Abstract:

Aiming at the problems of multi-UAV formation collision avoidance, formation recovery and the consistency of position and velocity convergence, a distributed cooperative formation control algorithm based on the improved potential field principle and consistency theory is proposed. The static obstacle model, UAV particle model and the second-order system dynamic model are established; the coordination potential field function with coordination factors and communication weights is defined, which can achieve the control objectives of collision avoidance and formation recovery; on the basic consistency protocol, the formation center reference vector, expected speed and speed stabilization items are introduced to achieve the convergence and consistency of position and speed; the coordinated formation control algorithm is designed by combining the improved consistency protocol and the improved total acceleration under the action of the potential field, and the stable convergence of the algorithm is proved by the Hamilton function. The simulation results show that the method can achieve the control objectives of collision avoidance, formation recovery and the convergence of position and velocity.

Key words: coordinated formation, coordination potential field function, communication weight, formation recovery, consensus algorithm

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