AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
Article Link
Collect
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Full Length Article | Open Access

Load distribution strategy for multi-lift system with helicopters based on power consumption and robust adaptive game control

Dengyan DUANGen LENGJie GAOXinming FENGJianbo LI,( )
National Key Laboratory of Rotorcraft Aeromechanics, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China

Peer review under responsibility of Editorial Committee of CJA.

Show Author Information

Abstract

It is of great significance to reasonably distribute the slung load to each helicopter while considering difference in power consumption, relative position and interaction comprehensively. Therefore, the load distribution strategy based on power consumption and robust adaptive game control is proposed in this paper. The study is on a “2-lead” multi-lift system of four tandem helicopters carrying a load cooperatively. First, based on the hierarchical control, the load distribution problem is divided into two parts: the calculation of expected cable force and the calculation of the anti-disturbance cable force. Then, aimed at minimizing the maximum equivalent power of helicopter, an optimization problem is set up to calculate the expected cable force. Specially, the agent power model is trained by BP neural network, the safe distance constraint between helicopters is set to 2.5 rotor diameters to reduce aerodynamic interference, and the helicopters with different performance can be considered by introducing the equivalent power factor into the objective function. Next, considering the difference and interaction between helicopters, the robust adaptive differential game control is proposed to calculate the anti-disturbance cable force. Particularly, to solve the coupled Hamiltonian equations, an adaptive solving method for value function is proposed, and its stability is proved in the sense of Lyapunov. The simulation results indicate that the proposed load distribution method based on power consumption is applicable to the entire flight trajectory even there are differences between helicopters. The game control can consider interaction between helicopters, can deal with different objective functions, and has strong robustness and small steady-state error. Based on the entire strategy, the cable force can be reasonably allocated so as to resist disturbance and improve the flight performance of the whole system.

Electronic Supplementary Material

Download File(s)
cja-36-4-268_ESM.pdf (92.5 KB)

References

1
Ronen T, A BRYSON J Jr, Hindson W. Dynamics of a helicopter with a sling load. 13th Atmospheric Flight Mechanics Conference. 1986 August 18-20; Williamsburg, USA. Reston: AIAA; 1986.
2

Cicolani LS, Kanning G, Synnestvedt R. Simulation of the dynamics of helicopter slung load systems. J Am Helicopter Soc 1995;40:44–61.

3
Bisgaard M. Modeling, estimation, and control of helicopter slung load system[dissertation]. Aalborg: Aalborg University; 2008.
4

Bisgaard M, la Cour-Harbo A, Dimon BJ. Adaptive control system for autonomous helicopter slung load operations. Control Eng Pract 2010;18:800–11.

5
Cicolani LS. Equations of motion of slung-load systems, including multilift systems. Washington. D.C.: NASA; 1992.
6

Raz R, Rosen A. Trim and stability of a twin-lift system in forward flight. J Am Helicopter Soc 2005;50:138–49.

7
Yi K, He YQ, Han JD, et al. A review on control methods for multi-lift rotorcraft systems. 2018 IEEE 8th Annual International Conference on CYBER Technology in Automation, Control, and Intelligent Systems.2018 July 19-23; Tianjin, China.Piscataway: IEEE Press;2018.
8
Bernard M. A system of autonomously flying helicopters for load transportation [dissertation]. Thüringer Wald: Ilmenau University of Technology; 2013.
9
Berrios M, Takahashi M, Whalley M, et alLoad distribution control and swing angle feedback for an autonomous dual lift system with flight test results. Phoenix, USA. Fairfax: American Helicopter Society (AHS); 2018. p. 1–13.
10
Geng JY, Langelaan JW. Implementation and demonstration of coordinated transport of a slung load by a team of rotorcraft. AIAA Scitech 2019 Forum. 2019 January 7-11; San Diego, USA. Reston: AIAA; 2019.
11

Geng JY, Langelaan JW. Cooperative transport of a slung load using load-leading control. J Guid Control Dyn 2020;43:1313–31.

12

Duan DY, Zhao H, Yu TL, et al. Application of social spider optimization and improved active disturbance rejection controller in hierarchical control of cooperative multi-lift with four unmanned helicopters. Proc Inst Mech Eng Part G J Aerosp Eng 2022;236:671–84.

13
Geng J. Control, estimation and planning for coordinated transport of a slung load by a team of aerial robots [dissertation].University Park. The Pennsylvania State University; 2020.
14
Geng JY, Singla P, Langelaan JW. Trajectory planning and control for a multilift system based on load distribution. AIAA Scitech 2021 Forum.2021 January 11-15; Nashville, USA. Reston: AIAA; 2021.
15

Enciu J, Horn JF. Flight performance optimization of a multilift rotorcraft formation. J Aircr 2017;54:1521–38.

16
Song Y, Horn JF, Li Z, et al. Modeling, simulation, and nonlinear control of a rotorcraft multi-lift system. Proceedings of Annual Forum Proceedings, 69th American Helicopter Society International Annual Forum. 2013 May 21-23; Phoenix, USA. Alexandria: AHS International; 2013.
17

Gimenez J, Salinas LR, Gandolfo DC, et al. Control for cooperative transport of a bar-shaped payload with rotorcraft UAVs including a landing stage on mobile robots. Int J Syst Sci 2020;51:3378–92.

18

Arab F, Shirazi FA, Yazdi MRH. Planning and distributed control for cooperative transportation of a non-uniform slung-load by multiple quadrotors. Aerosp Sci Technol 2021;117 106917.

19
Chopra O, Ghose D. Distributed control for multiple UAV transport of slung loads. AIAA SCITECH 2022 Forum. 2022 January 3-7; San Diego, USA. Reston: AIAA; 2022.
20

Jimenez-Lizarraga M, Garcia O, Chapa-Garcia R, et al. Differential game-based formation flight for quadrotors. Int J Control Autom Syst 2018;16:1854–65.

21
Jiang LW, Gonzalez F, McFadyen A. Cooperative game theory based multi-UAV consensus-based formation control. Athens, Greece. Piscataway: IEEE Press; 2020.
22

Chai Y, Luo JJ, Han N, et al. Robust event-triggered game-based attitude control for on-orbit assembly. Aerosp Sci Technol 2020;103 105894.

23
Cicolani L, Kanning G. A comprehensive estimate of the static aerodynamic forces and moments of the 8-by 8-by 20-Foot cargo container. Washington, C: NASA; 1987.
24

Cicolani LS, da Silva JGA, Duque EPN, et al. Unsteady aerodynamic model of a cargo container for slung-load simulation. Aeronaut J 2004;108:357–68.

25

Cicolani LS, Cone A, Theron JN, et al. Flight test and simulation of a cargo container slung load in forward flight. J Am Helicopter Soc 2009;54:32006–618.

26

Mahmuddin F. Rotor blade performance analysis with blade element momentum theory. Energy Procedia 2017;105:1123–9.

27

Duan D, Li Y, Ding Z, et al. Flight dynamics analysis of a small tandem helicopter considering aerodynamic interference. Proc Inst Mech Eng, Part G: J Aerosp Eng 2022;236:2803–16.

28
Gaonkar G, Peters D. Review of dynamic inflow modeling for rotorcraft flight dynamics. 27th Structures, Structural Dynamics and Materials Conference. 1986 May 19-21 May;San Antonio, USA. Reston: AIAA; 1986.
29
Padfield GD. Helicopter flight dynamics: The theory and application of flying qualities and simulation modelling. 2nd. New York: John Wiley & Sons; 2008. p. 87–184.
30

Duivenvoorden R, Voskuijl M, Morée L, et al. Numerical and experimental investigation into the aerodynamic benefits of rotorcraft formation flight. J Am Helicopter Soc 2022;67:1–17.

31
Jain KP, Fortmuller T, Byun J, et al. Modeling of aerodynamic disturbances for proximity flight of multirotors. 2019 International Conference on Unmanned Aircraft Systems (ICUAS).2019 June 11-14; Atlanta, USA. Piscataway: IEEE;2019.
32

Shi GY, Hönig W, Yue YS, et al. Neural-swarm: Decentralized close-proximity multirotor control using learned interactions. France. Piscataway:IEEE Press; 2020.

33

Cruz N, Jimenez-Lizarraga M. Finite time robust feedback Nash equilibrium for linear quadratic games. IFAC-PapersOnLine 2017;50:11794–9.

Chinese Journal of Aeronautics
Pages 268-285
Cite this article:
DUAN D, LENG G, GAO J, et al. Load distribution strategy for multi-lift system with helicopters based on power consumption and robust adaptive game control. Chinese Journal of Aeronautics, 2023, 36(4): 268-285. https://doi.org/10.1016/j.cja.2023.01.001

29

Views

1

Crossref

1

Web of Science

2

Scopus

Altmetrics

Received: 25 January 2022
Revised: 09 August 2022
Accepted: 30 October 2022
Published: 12 January 2023
© 2023 Chinese Society of Aeronautics and Astronautics.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Return