The present paper introduces an adaptive non-singular fast terminal sliding mode control (ANFTSMC) combined with a finite-time disturbance observer (FTDO), designed to address the trajectory tracking problem of a quadrotor system under the influence of external perturbations, model uncertainties, and mass variations. First, the nonlinear simplified dynamic model of the quadrotor is derived using the Newton-Euler approach. Then, an ANFTSMC method is employed to formulate control strategies for both the inner and outer loops of the quadrotor system. Backpropagation laws are used to tune the gains of the discontinuous reaching law. In addition, the paper integrates a finite-time disturbance observer with the proposed approach to estimate and counteract external disturbances. The closed-loop control stability is verified using Lyapunov theory. To assess the effectiveness of the suggested method, multiple flight tests are proposed using numerical simulations carried out in MATLAB/SIMULINK software. Simulation results are compared with an adaptive nonsingular fast terminal sliding mode controller (ANFTSMC). Numerical simulations demonstrate the superior performance of the suggested approach in terms of convergence time, tracking precision, and ability to reject external disturbances and uncertainties.
YuXFengYManZ.Terminal sliding mode control – an overview. IEEE Open J Ind Electron Soc2021; 2: 36–52.
2.
TangY.Terminal sliding mode control for rigid robots. Automatica1998; 34(1): 51–56.
3.
FengYYuXManZ.Non-singular terminal sliding mode control of rigid manipulators. Automatica2002; 38(12): 2159–2167.
4.
XinghuoYZhihongM.Fast terminal sliding-mode control design for nonlinear dynamical systems. IEEE Trans Circuits Syst I Fundam Theory Appl2002; 49(2): 261–264.
5.
LabbadiMDjemaiMBoubakerS.A novel non-singular terminal sliding mode control combined with integral sliding surface for perturbed quadrotor. Proc IMechE, Part I: J Systems and Control Engineering2022; 236(5): 999–1009.
6.
AlqaisiWKaliYGhommamJ, et al. Position and attitude tracking of uncertain quadrotor unmanned aerial vehicles based on non-singular terminal super-twisting algorithm. Proc IMechE, Part I: J Systems and Control Engineering2020; 234(3): 396–408.
7.
ChenJLongYLiT, et al. Attitude tracking control for quadrotor based on time-varying gain extended state observer. Proc IMechE, Part I: J Systems and Control Engineering2023; 237(4): 585–595.
8.
Díaz-MéndezYde JesusLDde SousaMS, et al. Conditional integrator sliding mode control of an unmanned quadrotor helicopter. Proc IMechE, Part I: J Systems and Control Engineering2022; 236(3): 458–472.
9.
SoorkiMNMoghaddamTVEmamifardA. A new fast finite time fractional order adaptive sliding-mode control for a quadrotor. In: 2021 7th international conference on control, instrumentation and automation (ICCIA), Tabriz, Iran, February 2021, pp.1–5. New York, NY: IEEE. DOI: 10.1109/ICCIA52082.2021.9403563.
10.
HuMLeeKAhnH, et al. Stabilization and tracking of a quadrotor using modified sigmoid sliding mode control. Sensors2022; 22(10): 3618.
11.
LeeKKimSKwakS, et al. Quadrotor stabilization and tracking using nonlinear surface sliding mode control and observer. Appl Sci2021; 11(4): 1417.
12.
TsaiS-HChangY-PLinH-Y, et al. Design and implementation of integral backstepping sliding mode control for quadrotor trajectory tracking. Processes2021; 9(11): 1951.
13.
NekoukarVMahdian DehkordiN.Robust path tracking of a quadrotor using adaptive fuzzy terminal sliding mode control. Control Eng Pract2021; 110: 104763.
14.
ZareMPazookiFHaghighiSE.Quadrotor UAV position and altitude tracking using an optimized fuzzy-sliding mode control. IETE J Res2022; 68(6): 4406–4420.
15.
WangTParwanaHUmemotoK, et al. Non-cascade adaptive sliding mode control for quadrotor UAVs under parametric uncertainties and external disturbance with indoor experiments. J Intell Robot Syst2021; 102(1): 8.
16.
HoumYEAbbouAAggaA.Design of a modified terminal sliding mode controller with time varying delayed output observer for a quad-rotor system. IFAC-PapersOnLine2022; 55(12): 408–413.
17.
El HoumYAbbouALabbadiM, et al. Optimal new sliding mode controller combined with modified supertwisting algorithm for a perturbed quadrotor UAV. Int J Aerosp Eng2020; 2020: 1–10.
18.
MaqsoodHQuY.Nonlinear disturbance observer based sliding mode control of quadrotor helicopter. J Electr Eng Technol2020; 15(3): 1453–1461.
19.
BenaddyALabbadiMBouziM.Robust flight control for a quadrotor under external disturbances based on generic second order sliding mode control. IFAC-PapersOnLine2022; 55(12): 270–275.
20.
GurumurthyGDasDK.Terminal sliding mode disturbance observer based adaptive super twisting sliding mode controller design for a class of nonlinear systems. Eur J Control2021; 57: 232–241.
21.
LiCWangYYangX.Adaptive fuzzy control of a quadrotor using disturbance observer. Aerosp Sci Technol2022; 128: 107784.
22.
JingYWangXHeredia-JuesasJ, et al. PX4 simulation results of a quadcopter with a disturbance-observer-based and PSO-optimized sliding mode surface controller. Drones2022; 6(9): 261.
23.
XiongJ-JZhangG-B.Global fast dynamic terminal sliding mode control for a quadrotor UAV. ISA Trans2017; 66: 233–240.
24.
LiSWangYTanJ, et al. Adaptive RBFNNs/integral sliding mode control for a quadrotor aircraft. Neurocomputing2016; 216: 126–134.
25.
HouZLuPTuZ.Nonsingular terminal sliding mode control for a quadrotor UAV with a total rotor failure. Aerosp Sci Technol2020; 98: 105716.
26.
HuangTHuangDWangZ, et al. Generic adaptive sliding mode control for a quadrotor UAV system subject to severe parametric uncertainties and fully unknown external disturbance. Int J Control Autom Syst2021; 19(2): 698–711.
27.
KangBMiaoYLiuF, et al. A second-order sliding mode controller of quad-rotor UAV based on PID sliding mode surface with unbalanced load. J Syst Sci Complex2021; 34(2): 520–536.
28.
HassaniHMansouriAAhaitoufA.Robust autonomous flight for quadrotor UAV based on adaptive nonsingular fast terminal sliding mode control. Int J Dyn Control2021; 9(2): 619–635.
29.
LiZMaXLiY.Robust tracking control strategy for a quadrotor using RPD-SMC and RISE. Neurocomputing2019; 331: 312–322.
30.
ZhuZXiaYFuM.Attitude stabilization of rigid spacecraft with finite-time convergence. Int J Robust Nonlinear Control2011; 21(6): 686–702.
31.
ZhangTJiaoXLinZ.Finite time trajectory tracking control of autonomous agricultural tractor integrated nonsingular fast terminal sliding mode and disturbance observer. Biosyst Eng2022; 219: 153–164.
32.
NguyenNPMungNXThanhHLNN, et al. Adaptive sliding mode control for attitude and altitude system of a Quadcopter UAV via neural network. IEEE Access2021; 9: 40076–40085.
33.
ShiQLiXDongQ, et al. Composite finite-time adaptive anti-disturbance control for dynamic positioning of vessels with output constraints. Ocean Eng2022; 255: 111414.
34.
XuH.Finite-time stability analysis: a tutorial survey. Complexity2020; 2020(2020): 1–12.
35.
El HoumYAbbouAAggaA. Robust fixed time adaptive terminal sliding mode control of a QUAV under time varying disturbances and payload. Int J Intell Eng Syst2023; 16(3): 220–230.
