This article focuses on the vibration suppression and attitude tracking consensus control of multiple flapping wing unmanned aerial vehicles (UAVs) in the presence of external disturbances and time varying actuator faults. Each flapping wing UAV equipped with a rigid-flexible coupled wing is modeled as partial differential equations (PDEs) with spatially varying coefficients. The hyperbolic tangent function is introduced to deal with the effect of external disturbances. The proposed disturbance rejection approach does not require prior knowledge of external disturbances. Adaptive tuning techniques are adopted to compensate for the system uncertainties caused by time varying actuator faults and external disturbances. A novel distributed fault tolerant boundary control is developed based on the connected and undirected graph to maintain the attitude consensus of multiple flapping wing UAVs and synchronously offset the vibrations of each flapping wing UAV. The uniformly bounded stability of multiple flapping wing UAVs with the designed control protocol is demonstrated by rigorous Lyapunov stability analysis. The control performance of the proposed approach is validated by simulations.
ChenQFangYCLiYP (2022) Neural network-based hybrid three-dimensional position control for a flapping wing aerial vehicle. IEEE Transactions on Cybernetics53(10): 6095–6108.
2.
GaoSLiuJK (2021) Adaptive fault-tolerant boundary vibration control for a flexible aircraft wing against actuator and sensor faults. Journal of Vibration and Control28(9–10): 1025–1034.
3.
HanFJiaY (2021) Bipartite consensus and distributed boundary control for multiple flexible manipulators associated with signed digraph. IEEE Transactions on Systems, Man, and Cybernetics: Systems52(5): 3005–3014.
4.
HeWMengTHeX, et al. (2018) Iterative learning control for a flapping wing micro aerial vehicle under distributed disturbances. IEEE Transactions on Cybernetics49(4): 1524–1535.
5.
HeWTangXWangT, et al. (2022) Trajectory tracking control for a three-dimensional flexible wing. IEEE Transactions on Control Systems Technology30(5): 2243–2250.
6.
HornRAJohnsonCR (1990) Matrix Analysis. Cambridge, UK: Cambridge University Press.
7.
JiNYangHLiuJK (2021) Coordination and vibration control for two sets of flexible satellites with input constraints and actuator failures. Journal of Vibration and Control27(11–12): 1281–1296.
8.
LiLLiuJK (2023) Consensus tracking control and vibration suppression for nonlinear mobile flexible manipulator multi-agent systems based on PDE model. Nonlinear Dynamics111(4): 3345–3359.
9.
LiYLiKTongS (2022) An observer-based fuzzy adaptive consensus control method for nonlinear multiagent systems. IEEE Transactions on Fuzzy Systems30(11): 4667–4678.
10.
LiLCaoFLiuJ (2023) Adaptive vibration control for constrained moving vehicle-mounted nonlinear 3D rigid-flexible manipulator system subject to actuator failures. Journal of Vibration and Control29(17–18): 4155–4171.
11.
LiuYGuoF (2018) Output feedback boundary control of a flexible marine riser system. Journal of Vibration and Control24(16): 3617–3630.
12.
LiuZHanZHeW (2021) Adaptive fault-tolerant boundary control of an autonomous aerial refueling hose system with prescribed constraints. IEEE Transactions on Automation Science and Engineering19(4): 2678–2688.
13.
LiuYYaoXZhaoW (2023a) Distributed neural-based fault-tolerant control of multiple flexible manipulators with input saturations. Automatica156: 111202.
14.
LiuZLuZZhaoZ, et al. (2023b) Single parameter adaptive neural network control for multi-agent deployment with prescribed tracking performance. Automatica156: 111207.
15.
MehdifarFBechlioulisCPHashemzadehF, et al. (2020) Prescribed performance distance-based formation control of multi-agent systems. Automatica119: 109086.
16.
MengTZhangYFuQ, et al. (2024) Observer-based adaptive control for a coupled PDE–ODE system of a flexible wing. IEEE Transactions on Systems, Man, and Cybernetics: Systems54(7): 3949–3959.
17.
ParanjapeAAGuanJChungSJ, et al. (2013) PDE boundary control for flexible articulated wings on a robotic aircraft. IEEE Transactions on Robotics29(3): 625–640.
18.
PolycarpouMMIoannouPA (1993) A robust adaptive nonlinear control design. In: Proceedings of American control conference, San Francisco, CA, 2–4 June 1993, 1365–1369.
19.
ShiTZhuF (2023) Security time-varying formation control for multi-agent systems under denial-of-service attacks via unknown input observer. IEEE Transactions on Network Science and Engineering10(4): 2372–2385.
20.
WaitmanSMarcosA (2020) H∞ control design for active flutter suppression of flexible-wing unmanned aerial vehicle demonstrator. Journal of Guidance, Control, and Dynamics43(4): 656–672.
21.
WangYSongYLewisFL (2015) Robust adaptive fault-tolerant control of multiagent systems with uncertain nonidentical dynamics and undetectable actuation failures. IEEE Transactions on Industrial Electronics62(6): 3978–3988.
22.
WangCWenCGuoL (2021) Adaptive consensus control for nonlinear multiagent systems with unknown control directions and time-varying actuator faults. IEEE Transactions on Automatic Control66(9): 4222–4229.
23.
YaoXQLiuYZhaoW (2022) Adaptive boundary vibration control and angle tracking consensus of networked flexible Timoshenko manipulator systems. IEEE Transactions on Systems, Man, and Cybernetics: Systems53(5): 2949–2960.
24.
YaoXQZhaoWLiuY (2023) Boundary control of multiple-sectioned flexible marine riser with time-varying output constraint. Journal of Vibration and Control29(19–20): 4785–4798.
25.
YuZQLiuZXZhangYM, et al. (2019) Distributed finite-time fault-tolerant containment control for multiple unmanned aerial vehicles. IEEE Transactions on Neural Networks and Learning Systems31(6): 2077–2091.
26.
YuYGuoJAhnCK, et al. (2022a) Neural adaptive distributed formation control of nonlinear multi-UAVs with unmodeled dynamics. IEEE Transactions on Neural Networks and Learning Systems34(11): 9555–9561.
27.
YuZQZhangYMJiangB, et al. (2022b) Refined fractional-order faulttolerant coordinated tracking control of networked fixed-wing UAVs against faults and communication delays via double recurrent perturbation FNNs. IEEE Transactions on Cybernetics54(2): 1189–1201.
28.
YuZQLiJXXuYW, et al. (2023) Reinforcement learning-based fractionalorder adaptive fault-tolerant formation control of networked fixed-wing UAVs with prescribed performance. IEEE Transactions on Neural Networks and Learning Systems35(3): 3365–3379.
29.
ZhangJYanJZhangP (2020) Multi-UAV formation control based on a novel back-stepping approach. IEEE Transactions on Vehicular Technology69(3): 2437–2448.
30.
ZhaoZJAhnCKLiHX (2019) Boundary antidisturbance control of a spatially nonlinear flexible string system. IEEE Transactions on Industrial Electronics67(6): 4846–4856.
31.
ZhaoZJZhangJLiuZ, et al. (2023) Adaptive quantized fault-tolerant control of a 2-DOF helicopter system with actuator fault and unknown dead zone. Automatica148: 110792.
32.
ZouAMFanZ (2020) Distributed fixed-time attitude coordination control for multiple rigid spacecraft. International Journal of Robust and Nonlinear Control30(1): 266–281.
