In this paper, a novel formation control scheme is presented by integrating the dynamic surface control for multi-quadrotor subject with model uncertainties and external disturbances. First, according to requirements of formation control, the target trajectories of followers are obtained by the designed virtual quadrotors. Then, the formation control problem is transformed into the trajectory tracking control problem. Second, the saturation function and the auxiliary system are developed to make up for nonlinear terms arising from input saturation. A nonlinear extended state observer (ESO) is proposed to estimate and compensate for model uncertainties and external disturbances, and a dynamic surface controller based on the nonlinear ESO is constructed for the desired formation performance. In addition, the amount of communications between the quadrotors is decreased by the constructed distributed speed estimator. And the uniformly ultimately bounded is proved by using the Lyapunov method. Finally, the numerical example is used to demonstrate that the designed controller is effective.
AslHJMahdiounSHYoonJ (2018) Vision-based control of an underactuated flying robot with input delay. Transactions of the Institute of Measurement and Control40(2): 446–455.
2.
BarikbinBFakharianA (2019) Trajectory tracking for quadrotor UAV transporting cable-suspended payload in wind presence. Transactions of the Institute of Measurement and Control41(5): 1243–1255.
3.
BishebanMLeeT (2021) Geometric adaptive control with neural networks for a quadrotor in wind fields. IEEE Transactions on Control Systems Technology29(4): 1533–1548.
4.
CaoNLynchAF (2016) Inner-outer loop control for quadrotor UAVs with input and state constraints. IEEE Transactions on Control Systems Technology24(5): 1797–1804.
5.
CaoXShenZ (2018) Dynamic surface trajectory tracking control for quadrotor UAV with prescribed performance. In: 2018 IEEE international conference on information and automation (ICIA), Wuyishan, China, 11–13 August, pp. 214–219. New York: IEEE.
6.
CastilloASanzRGarciaP, et al. (2019) Disturbance observer-based quadrotor attitude tracking control for aggressive maneuvers. Control Engineering Practice82: 14–23.
7.
DaiSLHeSChenX, et al. (2020) Adaptive leaderfollower formation control of nonholonomic mobile robots with prescribed transient and steady-state performance. IEEE Transactions on Industrial Informatics16(6): 3662–3671.
8.
DouJKongXChenX, et al. (2017) Output feedback observer-based dynamic surface controller for quadrotor UAV using quaternion representation. Proceedings of the Institution of Mechanical Engineers Part G: Journal of Aerospace Engineering231(14): 2537–2548.
9.
DunAWangRXuQ (2020) Leader-follower formation control of multi-quadrotor systems based on the dynamic surface approach. In: 2020 Chinese Automation Congress (CAC), Shanghai, China, 6–8 November, pp. 572–577. New York: IEEE.
10.
FuJWenGYuW, et al. (2019) Consensus of second-order multiagent systems with both velocity and input constraints. IEEE Transactions on Industrial Electronics66(10): 7946–7955.
11.
GuoQLiXZuoZ, et al. (2021) Quasi-synchronization control of multiple electrohydraulic actuators with load disturbance and uncertain parameters. IEEE/ASME Transactions on Mechatronics26(4): 2048–2058.
12.
GuoQZhangYCellerBG, et al. (2018a) State-constrained control of single-rod electrohydraulic actuator with parametric uncertainty and load disturbance. IEEE Transactions on Control Systems Technology26(6): 2242–2249.
13.
GuoYJiangBZhangY (2018b) A novel robust attitude control for quadrotor aircraft subject to actuator faults and wind gusts. IEEE/CAA Journal of Automatica Sinica5(1): 292–300.
14.
LazimIMHusainARMohamedZ, et al. (2019) Disturbance observer-based formation tracking control of multiple quadrotors in the presence of disturbances. Transactions of the Institute of Measurement and Control41(14): 4129–4141.
15.
LiBBanHGongW, et al. (2020) Extended state observer-based finite-time dynamic surface control for trajectory tracking of a quadrotor unmanned aerial vehicle. Transactions of the Institute of Measurement and Control42(15): 2956–2968.
16.
LiZWenGDuanZ, et al. (2015) Designing fully distributed consensus protocols for linear multi-agent systems with directed graphs. IEEE Transactions on Automatic Control60(4): 1152–1157.
17.
LinZFrancisBMaggioreM (2005) Necessary and sufficient graphical conditions for formation control of unicycles. IEEE Transactions on Automatic Control50(1): 121–127.
18.
LiuCLiuXWangH, et al. (2021) Adaptive control and application for nonlinear systems with input nonlinearities and unknown virtual control coefficients. IEEE Transactions on Cybernetics. Epub ahead of print 4March. DOI: 10.1109/TCYB.2021.3054373.
19.
LiuHMaTLewisFL, et al. (2020a) Robust formation trajectory tracking control for multiple quadrotors with communication delays. IEEE Transactions on Control Systems Technology28(6): 2633–2640.
20.
LiuYHuangPZhangF, et al. (2020b) Distributed formation control using artificial potentials and neural network for constrained multiagent systems. IEEE Transactions on Control Systems Technology28(2): 697–704.
21.
LuKYangZLiaoL, et al. (2021) Extended state observer-based robust control of an omnidirectional quadrotor with tiltable rotors. Transactions of the Institute of Measurement and Control43(5): 1143–1155.
22.
MiladiNDimassiHSaidSH, et al. (2020) Explicit nonlinear model predictive control tracking control based on a sliding mode observer for a quadrotor subject to disturbances. Transactions of the Institute of Measurement and Control42(2): 214–227.
23.
ModirroustaAKhodabandehM (2017) Adaptive non-singular terminal sliding mode controller: New design for full control of the quadrotor with external disturbances. Transactions of the Institute of Measurement and Control39(3): 371–383.
24.
Mohd BasriMAHusainARDanapalasingamKA (2015) Intelligent adaptive backstepping control for MIMO uncertain non-linear quadrotor helicopter systems. Transactions of the Institute of Measurement and Control37(3): 345–361.
25.
OrtizJPMinchalaLIReinosoMJ (2016) Nonlinear robust h-infinity PID controller for the multivariable system quadrotor. IEEE Latin America Transactions14(3): 1176–1183.
26.
ParkJKimYKimS (2015) Landing site searching and selection algorithm development using vision system and its application to quadrotor. IEEE Transactions on Control Systems Technology23(2): 488–503.
27.
PrajapatiAKPrasadR (2021) A novel order reduction method for linear dynamic systems and its application for designing of PID and lead/lag compensators. Transactions of the Institute of Measurement and Control43(5): 1226–1238.
28.
RenWBeardR (2005) Consensus seeking in multiagent systems under dynamically changing interaction topologies. IEEE Transactions on Automatic Control50(5): 655–661.
29.
RyllMBoffHHGiordanoPR (2015) A novel overactuated quadrotor unmanned aerial vehicle: Modeling, control, and experimental validation. IEEE Transactions on Control Systems Technology23(2): 540–556.
30.
SaggaiAZeghlacheSBenyettouL, et al. (2021) Fault tolerant control against actuator faults based on interval type-2 fuzzy sliding mode controller for a quadrotor aircraft. In: 2020 2nd international workshop on human-centric smart environments for health and well-being (IHSH), Boumerdes, Algeria, 9–10 February, pp. 181–186. DOI: 10.1109/IHSH51661.2021.9378754.
31.
ShenZLiFCaoX, et al. (2021) Prescribed performance dynamic surface control for trajectory tracking of quadrotor UAV with uncertainties and input constraints. International Journal of Control94: 2945–2955.
32.
SiddhardhaK (2019) Autonomous reduced-gravity enabling quadrotor test-bed: Design, modelling and flight test analysis. Aerospace Science and Technology86: 64–77.
33.
SiyuHXugangWYinZ (2020) Sliding-mode control for a rolling-missile with input constraints. Journal of Systems Engineering and Electronics31(5): 1041–1050.
34.
SoltanpourMRHasanvandFHooshmandR (2020) Robust linear parameter varying attitude control of a quadrotor unmanned aerial vehicle with state constraints and input saturation subject to wind disturbance. Transactions of the Institute of Measurement and Control42(6): 1083–1096.
35.
SwaroopDHedrickJYipP, et al. (2000) Dynamic surface control for a class of nonlinear systems. IEEE Transactions on Automatic Control45(10): 1893–1899.
36.
TanCKWangJPawYC, et al. (2016) Tracking of a moving ground target by a quadrotor using a backstepping approach based on a full state cascaded dynamics. Applied Soft Computing Journal47: 47–62.
37.
XuDCaoK (2019) Formation control of quadrotors for maneuver flight based on exponential observer. In: Proceedings of 2018 5th IEEE international conference on cloud computing and intelligence systems, Nanjing, China, 23–25 November, pp. 33–37. New York: IEEE.
38.
YangHChengLXiaY, et al. (2018) Active disturbance rejection attitude control for a dual closed-loop quadrotor under gust wind. IEEE Transactions on Control Systems Technology26(4): 1400–1405.
39.
YangLLiBLiW, et al. (2020) Concrete defects inspection and 3D mapping using cityflyer quadrotor robot. IEEE/CAA Journal of Automatica Sinica7(4): 991–1002.
40.
YuGCabecinhasDCunhaR, et al. (2019) Nonlinear backstepping control of a quadrotor-slung load system. IEEE/ASME Transactions on Mechatronics24(5): 2304–2315.
41.
YuYGuoYPanX, et al. (2015) Robust backstepping tracking control of uncertain MIMO nonlinear systems with application to quadrotor UAVs. In: 2015 IEEE international conference on information and automation, Lijiang, China, 8–10 August, pp. 2868–2873. DOI: 10.1109/ICInfA.2015.7279776.
42.
ZhangYChenZSunM (2020) Trajectory tracking control for a quadrotor unmanned aerial vehicle based on dynamic surface active disturbance rejection control. Transactions of the Institute of Measurement and Control42(12): 2198–2205.
43.
ZhangYChenZZhangX, et al. (2018) A novel control scheme for quadrotor UAV based upon active disturbance rejection control. Aerospace Science and Technology79: 601–609.
44.
ZhaoKZhangJMaD, et al. (2020) Composite disturbance rejection attitude control for quadrotor with unknown disturbance. IEEE Transactions on Industrial Electronics67(8): 6894–6903.
45.
ZhouFZhouYJJiangGP, et al. (2018) Adaptive tracking control of quadrotor UAV system with input constraints. In: 2018 Chinese control and decision conference (CCDC), Shenyang, China, 9–11 June, pp. 5774–5779. New York: IEEE.
