基于改进平衡优化算法的折叠翼飞行器自抗扰控制器设计

孟志鹏; 杨柳庆; 王波; 刘燕斌

doi:10.13700/j.bh.1001-5965.2022.0698

基于改进平衡优化算法的折叠翼飞行器自抗扰控制器设计

doi: 10.13700/j.bh.1001-5965.2022.0698

1.
军事科学院国防科技创新研究院，北京 100071
2.
南京航空航天大学无人机研究院，南京 210016
3.
南京航空航天大学航天学院，南京 210016

详细信息

通讯作者:
E-mail：yangliuqing@nuaa.edu.cn

中图分类号: V249.1
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- 被引次数: 0
出版历程
- 收稿日期: 2022-08-09
- 录用日期: 2022-09-08
- 网络出版日期: 2022-09-21
- 整期出版日期: 2024-08-28

ADRC design for folding wing vehicles based on improved equilibrium optimization algorithm

1.
National Innovation Institute of Defense Technology，Academy of Military Sciences，Beijing 100071，China
2.
Research Institute of Pilotless Aircraft，Nanjing University of Aeronautics and Astronautics，Nanjing 210016，China
3.
College of Astronautics，Nanjing University of Aeronautics and Astronautics，Nanjing 210016，China

More Information

Corresponding author: E-mail：yangliuqing@nuaa.edu.cn

摘要

摘要:
针对折叠翼飞行器（FWV）模型误差和抗扰动能力较差及自抗扰控制器（ADRC）人工参数整定难的问题，提出一种基于莱维飞行的改进平衡优化（LEO）算法。给出典型FWV动力学模型，基于ADRC结构设计一种FWV的姿态控制器；在此基础上用所提算法整定了ADRC参数，并从控制性能和抗干扰的角度对经参数优化后的ADRC和传统ADRC进行仿真对比；将所提算法与经典平衡优化算法、粒子群优化（PSO）算法等进行仿真对比。仿真结果表明：所提算法优化的控制器能提高FWV的控制精度和扰动抑制性能，验证了所提算法在解决ADRC参数优化问题时的优越性。对搭载优化后ADRC的样机进行实飞验证，结果表明：在风扰之下，FWV样机仍具有较好的飞行性能指标，进一步验证了所提算法优化的ADRC对FWV抗扰能力的提升。
- 折叠翼飞行器 /
- 改进平衡优化算法 /
- 莱维飞行 /
- 自抗扰控制器 /
- 姿态控制
Abstract:
In view of the modeling errors and poor anti-disturbance ability of folding wing vehicles (FWV) and the difficulty in manual parameter setting of active disturbance rejection controllers (ADRC), an optimization algorithm based on improved equilibrium optimizer based on Lévy（LEO）was proposed. A dynamics model of typical FWV was established, and an attitude controller for the FWV was designed based on the ADRC structure. The parameters of the ADRC were adjusted by the proposed algorithm, and a comparison between the optimized ADRC and the traditional ADRC by the simulation was made from the perspective of control performance and anti-disturbance. The proposed algorithm was compared with the classical equilibrium optimizer, particle swarm optimization (PSO) algorithm, and so on. The simulation results show that the controller optimized by the proposed algorithm can improve the control accuracy and disturbance suppression performance of FWV, and the superiority of the algorithm in the parameter optimization of ADRC was verified. The prototype equipped with the improved ADRC was verified in real flight. The results show that the FWV prototype still has a good flight performance index under wind disturbance, which further verifies that ADRC optimized by the proposed algorithm improves the anti-disturbance of FWV.
- folding wing vehicle /
- improved equilibrium optimization algorithm /
- Levy flight /
- active disturbance rejection controller /
- attitude control

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图 1 FWV总体布局

Figure 1. Overall layout of FWV

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图 2 FWV操纵面

Figure 2. Control surface of FWV

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图 3 总体布置

Figure 3. General layout

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图 4 飞行器姿态控制器结构框图

Figure 4. Structure block diagram of attitude controller

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图 5 莱维飞行轨迹仿真

Figure 5. Simulation of Levy flight trajectory

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图 6 LEO算法流程图

Figure 6. Flow chart of LEO algorithm

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图 7 基于LEO算法的控制参数优化原理

Figure 7. Principle of control parameter optimization based on LEO algorithm

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图 8 攻角输出响应

Figure 8. Output response of angle of attack

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图 9 渐变风干扰下攻角跟踪曲线

Figure 9. Tracking curve of angle of attack under gradient disturbance

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图 10 适应度收敛曲线

Figure 10. Convergence curves of fitness

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图 11 攻角输出响应曲线

Figure 11. Output response curves of angle of attack

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图 12 适应度值分布箱线

Figure 12. Boxplot of fitness value distribution

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图 13 ${\beta _{01}}$箱线

Figure 13. Boxplot of ${\beta _{01}}$

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图 14 ${\beta _{02}}$箱线

Figure 14. Boxplot of ${\beta _{02}}$

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图 15 ${\beta _{03}}$箱线

Figure 15. Boxplot of ${\beta _{03}}$

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图 16 ${\beta _1}$箱线

Figure 16. Boxplot of ${\beta _1}$

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图 17 ${\beta _2}$箱线

Figure 17. Boxplot of ${\beta _2}$

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图 18 LEO-ESO观测下攻角通道扰动

Figure 18. Disturbance of angle of attack channel under LEO-ESO

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图 19 样机出筒

Figure 19. Prototype launched from cylinder

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图 20 样机实飞

Figure 20. Real flight drawing of prototype

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图 21 PID样机攻角响应

Figure 21. Angle of attack response of PID prototype

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图 22 LEO-ADRC样机攻角响应

Figure 22. Angle of attack response of LEO-ADRC prototype

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表 1 控制参数优化前后

Table 1. Control parameters before and after optimization

控制器	${\beta _{01}}$	${\beta _{02}}$	${\beta _{03}}$	${\beta _1}$	${\beta _2}$
ADRC	100.00	60 000.00	1 000 000.00	2 500.00	134.00
LEO算法优化后 ADRC	300.00	50 415.00	897 390.00	10 000	134

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表 2 算法优化速度信息

Table 2. Speed informations of algorithm optimization

算法	平均优化时间/s
LEO	4.89
EO^[16]	8.12
PSO^[18]	5.64
GWO^[19]	4.95
WOA^[20]	6.31

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