CLC number: TP273
On-line Access: 2019-06-10
Received: 2018-09-15
Revision Accepted: 2019-03-20
Crosschecked: 2019-05-13
Cited: 0
Clicked: 5971
Zi-quan Yu, Zhi-xiang Liu, You-min Zhang, Yao-hong Qu, Chun-yi Su. Decentralized fault-tolerant cooperative control of multiple UAVs with prescribed attitude synchronization tracking performance under directed communication topology[J]. Frontiers of Information Technology & Electronic Engineering, 2019, 20(5): 685-700.
@article{title="Decentralized fault-tolerant cooperative control of multiple UAVs with prescribed attitude synchronization tracking performance under directed communication topology",
author="Zi-quan Yu, Zhi-xiang Liu, You-min Zhang, Yao-hong Qu, Chun-yi Su",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="20",
number="5",
pages="685-700",
year="2019",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.1800569"
}
%0 Journal Article
%T Decentralized fault-tolerant cooperative control of multiple UAVs with prescribed attitude synchronization tracking performance under directed communication topology
%A Zi-quan Yu
%A Zhi-xiang Liu
%A You-min Zhang
%A Yao-hong Qu
%A Chun-yi Su
%J Frontiers of Information Technology & Electronic Engineering
%V 20
%N 5
%P 685-700
%@ 2095-9184
%D 2019
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.1800569
TY - JOUR
T1 - Decentralized fault-tolerant cooperative control of multiple UAVs with prescribed attitude synchronization tracking performance under directed communication topology
A1 - Zi-quan Yu
A1 - Zhi-xiang Liu
A1 - You-min Zhang
A1 - Yao-hong Qu
A1 - Chun-yi Su
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 20
IS - 5
SP - 685
EP - 700
%@ 2095-9184
Y1 - 2019
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/FITEE.1800569
Abstract: In this paper, a decentralized fault-tolerant cooperative control scheme is developed for multiple unmanned aerial vehicles (UAVs) in the presence of actuator faults and a directed communication network. To counteract in-flight actuator faults and enhance formation flight safety, neural networks (NNs) are used to approximate unknown nonlinear terms due to the inherent nonlinearities in UAV models and the actuator loss of control effectiveness faults. To further compensate for NN approximation errors and actuator bias faults, the disturbance observer (DO) technique is incorporated into the control scheme to increase the composite approximation capability. Moreover, the prediction errors, which represent the approximation qualities of the states induced by NNs and DOs to the measured states, are integrated into the developed fault-tolerant cooperative control scheme. Furthermore, prescribed performance functions are imposed on the attitude synchronization tracking errors, to guarantee the prescribed synchronization tracking performance. One of the key features of the proposed strategy is that unknown terms due to the inherent nonlinearities in UAVs and actuator faults are compensated for by the composite approximators constructed by NNs, DOs, and prediction errors. Another key feature is that the attitude synchronization tracking errors are strictly constrained within the prescribed bounds. Finally, simulation results are provided and have demonstrated the effectiveness of the proposed control scheme.
[1]Bayezit I, Fidan B, 2013. Distributed cohesive motion control of flight vehicle formations. IEEE Trans Ind Electron, 60(12):5763-5772.
[2]Bechlioulis CP, Rovithakis GA, 2008. Robust adaptive control of feedback linearizable MIMO nonlinear systems with prescribed performance. IEEE Trans Autom Contr, 53(9):2090-2099.
[3]Bechlioulis CP, Rovithakis GA, 2010. Prescribed performance adaptive control for multi-input multi-output affine in the control nonlinear systems. IEEE Trans Autom Contr, 55(5):1220-1226.
[4]Chen M, Ge SS, Ren B, 2011. Adaptive tracking control of uncertain MIMO nonlinear systems with input constraints. Automatica, 47(3):452-465.
[5]Du J, Hu X, Krstić M, et al., 2016. Robust dynamic positioning of ships with disturbances under input saturation. Automatica, 73:207-214.
[6]Han Z, Lin Z, Fu M, et al., 2015. Distributed coordination in multi-agent systems: a graph Laplacian perspective. Front Inform Technol Electron Eng, 16(6):429-448.
[7]He L, Sun X, Lin Y, 2016. Distributed output-feedback formation tracking control for unmanned aerial vehicles. Int J Syst Sci, 47(16):3919-3928.
[8]Li Y, Wang C, Hu Q, 2017. Adaptive control with prescribed tracking performance for hypersonic flight vehicles in the presence of unknown elevator faults. Int J Contr, in press.
[9]Liao F, Teo R, Wang JL, et al., 2017. Distributed formation and reconfiguration control of VTOL UAVs. IEEE Trans Contr Syst Technol, 25(1):270-277.
[10]Lin W, 2014. Distributed UAV formation control using differential game approach. Aerosp Sci Technol, 35:54-62.
[11]Liu ZX, Yuan C, Zhang YM, et al., 2016. A learning-based fault tolerant tracking control of an unmanned quadrotor helicopter. J Intell Robot Syst, 84(1-4):145-162.[doi:10.1007/s10846-015-0293-0]
[12]Liu ZX, Yuan C, Yu X, et al., 2017. Retrofit fault-tolerant tracking control design of an unmanned quadrotor helicopter considering actuator dynamics. Int J Rob Nonl Contr, in press.
[13]Nigam N, Bieniawski S, Kroo I, et al., 2012. Control of multiple UAVs for persistent surveillance: algorithm and flight test results. IEEE Trans Contr Syst Technol, 20(5):1236-1251.
[14]Qian M, Jiang B, Liu HHT, 2016. Dynamic surface active fault tolerant control design for the attitude control systems of UAV with actuator fault. Int J Contr Autom Syst, 14(3):723-732.
[15]Ren W, Beard RW, Atkins EM, 2007. Information consensus in multivehicle cooperative control. IEEE Contr Syst, 27(2):71-82.
[16]Shi J, Yang Y, Sun J, et al., 2017. Fault-tolerant formation control of non-linear multi-vehicle systems with application to quadrotors. IET Contr Theory Appl, 11(17):3179-3190.
[17]Waharte S, Trigoni N, 2010. Supporting search and rescue operations with UAVs. Int Conf on Emerging Security Technologies, p.142-147.
[18]Wang B, Zhang Y, 2018. An adaptive fault-tolerant sliding mode control allocation scheme for multirotor helicopter subject to simultaneous actuator faults. IEEE Trans Ind Electron, 65(5):4227-4236.
[19]Wu B, Wang D, Poh EK, 2011. Decentralized robust adaptive control for attitude synchronization under directed communication topology. J Guid Contr Dynam, 34(4):1276-1282.
[20]Xu Q, Yang H, Jiang B, et al., 2014. Fault tolerant formations control of UAVs subject to permanent and intermittent faults. J Intell Robot Syst, 73(1-4):589-602.
[21]Xue R, Song J, Cai G, 2016. Distributed formation flight control of multi-UAV system with nonuniform time-delays and jointly connected topologies. Proc Inst Mech Eng Part G: J Aerosp Eng, 230(10):1871-1881.
[22]Yan M, Zhu X, Zhang X, et al., 2017. Consensus-based three-dimensional multi-UAV formation control strategy with high precision. Front Inform Technol Electron Eng, 18(7):968-977.
[23]Yu X, Liu ZX, Zhang YM, 2016. Fault-tolerant formation control of multiple UAVs in the presence of actuator faults. Int J Rob Nonl Contr, 26(12):2668-2685.
[24]Yu X, Li P, Zhang YM, 2018a. The design of fixed-time observer and finite-time fault-tolerant control for hypersonic gliding vehicles. IEEE Trans Ind Electron, 65(5):4135-4144.
[25]Yu X, Fu Y, Li P, et al., 2018b. Fault-tolerant aircraft control based on self-constructing fuzzy neural networks and multivariable SMC under actuator faults. IEEE Trans Fuzzy Syst, 26(4):2324-2335.
[26]Yu ZQ, Qu YH, Zhang YM, 2018. Safe control of trailing UAV in close formation flight against actuator fault and wake vortex effect. Aerosp Sci Technol, 77:189-205.
[27]Yuan C, Zhang YM, Liu ZX, 2015. A survey on technologies for automatic forest fire monitoring, detection, and fighting using unmanned aerial vehicles and remote sensing techniques. Can J For Res, 45(7):783-792.
[28]Zhang G, Sun Z, Zhang W, et al., 2017. MLP-based adaptive neural control of nonlinear time-delay systems with the unknown hysteresis. Int J Syst Sci, 48(8):1682-1691.
[29]Zhang YM, Jiang J, 2008. Bibliographical review on reconfigurable fault-tolerant control systems. Ann Rev Contr, 32(2):229-252.
[30]Zou A, Hou Z, Tan M, 2008. Adaptive control of a class of nonlinear pure-feedback systems using fuzzy backstepping approach. IEEE Trans Fuzzy Syst, 16(4):886-897.
Open peer comments: Debate/Discuss/Question/Opinion
<1>