电子电气工程与控制

基于量子行为鸽群优化的无人机紧密编队控制

  • 徐博 ,
  • 张大龙
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  • 哈尔滨工程大学 自动化学院, 哈尔滨 150001

收稿日期: 2019-12-12

  修回日期: 2020-01-06

  网络出版日期: 2020-02-06

基金资助

国家自然科学基金(61203225,61633008);中国博士后科学基金(2012M510083);黑龙江省自然科学基金(QC2014C069);装备发展部领域基金(61403110306)

Tight formation flight control of UAVs based on pigeon inspired algorithm optimization by quantum behavior

  • XU Bo ,
  • ZHANG Dalong
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  • College of automation, Harbin Engineering University, Harbin 150001, China

Received date: 2019-12-12

  Revised date: 2020-01-06

  Online published: 2020-02-06

Supported by

National Natural Science Foundation of China (61203225,61633008);China Postdoctoral Science Foundation (2012M510083);Natural Science Foundation of Heilongjiang Province (QC2014C069);Field Fund of Equipment Development Department (61403110306)

摘要

随着军事、民用需求的提高和相关领域的技术推动,无人机编队协同作业已成为当今人们逐渐关注的焦点。无人机紧密编队是指无人机间侧向距离在1~2倍翼展内的编队,因其可有效改善编队中无人机的气动性能而备受瞩目。基于无人机紧密编队条件下的气动耦合效应,建立三维空间下的状态空间方程描述双机相对运动,并推导了紧密编队条件下的双机最优编队构型,在此构型下将人工势场法和编队控制相结合作为控制系统中的间接控制环,并针对基本鸽群优化算法的寻优缺陷利用量子行为规则对其进行改进,将改进后的鸽群优化算法和无人机控制量结合作为控制系统中的直接控制环,最后通过仿真对比验证了此控制系统对于紧密编队控制的有效性。

本文引用格式

徐博 , 张大龙 . 基于量子行为鸽群优化的无人机紧密编队控制[J]. 航空学报, 2020 , 41(8) : 323722 -323722 . DOI: 10.7527/S1000-6893.2020.23722

Abstract

UAV tight formation refers to the formation whose lateral distance between the UAVs is within one to two times of the wingspan. It has attracted considerable attention because of its effective improvement in the aerodynamic performance of UAVs in formation. In this paper, the aerodynamic coupling effect of the UAVs in tight formation is studied, and the state-space equation in three-dimensional space is established to describe the relative motion of two UAVs. The optimal formation configuration of two UAVs in close formation is deduced, where the combination of the artificial potential field method and formation control is used as the indirect control loop in the control system, and the basic pigeon inspired opbimization algorithm is calculated. The optimization defect of the algorithm is improved by quantum behavior rules. The improved opbimization pigeon inspired algorithm and the UAV control variables are combined as the direct control loop in the control system. Finally, the effectiveness of the control system is verified by simulation comparisons.

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