Abstract
Quadrotors are highly maneuverable drones, which are susceptible to the parameter uncertainties such as the mass, drag coefficients, and moment of inertia. Whose nonlinearities, aerodynamic disturbances, and higher coupling between the rotational and the translational dynamics stand for a problem that demands a robust controller. In the present paper, a fractional order (FO) improved super twisting proportional-integral-derivative sliding-mode control (STPIDSMC) is proposed for the quadrotor system. To improve the speed tracking performance, a FOPIDSM surface is designed. Moreover, the proposed FO control approach ensures fast convergence, high precision, good robustness against stochastic perturbations and uncertainties. Finally, the performance of the FOSTPIDSMC is investigated under different scenarios. The simulation results clearly show the high control performance, efficiency and high disturbance rejection capacity of the controller strategy proposed in this work in comparison with the nonlinear internal model control (NLIMC) and FO backstepping sliding mode control (FOBSMC) strategies.
Similar content being viewed by others
Explore related subjects
Discover the latest articles and news from researchers in related subjects, suggested using machine learning.References
Mu, B., Zhang, K.: Integral Sliding Mode Flight Controller Design for A Quadrotor and The Application in A Heterogeneous Multi-Agent System. IEEE Trans. Ind. Electron., vol. 0046, no c (2017)
Shi, X.-N., Zhang, Y.-A.: D Zhou, ”Almost-global finite-time trajectory tracking control for quadrotors in the exponential coordinates. IEEE Trans. Aerosp. Electron. Syst. 53(1), 91–100 (2017)
Liu, H., Zhao, W., Zuo, Z., Zhong, Y.: Robust control for quadrotors with multiple Time-Varying uncertainties and delays. IEEE Trans. Ind. Electron. 64(2), 1303–1312 (2017)
Hua, C., Chen, J., Guan, X.: Fractional-order sliding mode control of uncertain QUAVs with time-varying state constraints. Nonlinear Dyn (2018)
Hassanalian, M., Abdelkefi, A.: Classifications, applications, and design challenges of drones: a review. Prog. Aerosp. Sci. 91(2016), 99–131 (2017)
Li, S., al.: Adaptive RBFNNs / integral sliding mode control for a quadrotor aircraft. Neurocomputing (2016)
Zuo, Z., Ru, P.: Augmented l1 adaptive tracking control of quadrotor unmanned aircrafts. IEEE Trans. Aerosp. Electron. Syst. 50(4), 3090–3101 (2014)
Hua, C., Chen, J., Guan, X.: Adaptive prescribed performance control of QUAVs with unknown time-varying payload and wind gust disturbance. J. Franklin Inst. 355(14), 6323–6338 (2018)
Zou, Y., Zhu, B: Adaptive Trajectory Tracking Controller for Quadrotor Systems Subject to Parametric Uncertainties. J Franklin Inst (2017)
Ai, X., Yu, J.: Fixed-time trajectory tracking for a quadrotor with external disturbances: a flatness-based sliding mode control approach. Aerosp. Sci. Technol. 89(58), 76 (2019)
Liu, H., Xi, J., Zhong, Y.: Robust attitude stabilization for nonlinear quadrotor systems with uncertainties and delays. IEEE Trans. Ind. Electron. 64(7), 5585–5594 (2017)
Mofid, O., Mobayen, S.: Adaptive sliding mode control for finite-time stability of quad-rotor UAVs with parametric uncertainties. ISA Trans (2017)
Ansari, U., Bajodah, A.H., Hamayun, M.T.: Quadrotor Control via robust generalized dynamic inversion and adaptive Non-Singular terminal sliding mode. Asian J. Control 21(4), 1–13 (2018)
Wang, H., Ye, X., Tian, Y., Zheng, G., Christov, N.: Model-free-based terminal SMC of quadrotor attitude and position. IEEE Trans. Aerosp. Electron. Syst. 52(5), 2519–2528 (2016)
Antonelli, G., Cataldi, E., Arrichiello, F., Giordano, P.R., Chiaverini, S., Franchi, A.: Adaptive Trajectory Tracking for Quadrotor MAVs in Presence of Parameter Uncertainties and External Disturbances. IEEE Trans. Ind. Electron. pp. 1–7 (2017)
Izaguirre-Espinosa, C., Muñoz-Vázquez, A. J., Sánchez-Orta, A., Parra-Vega, V., Castillo, P.: Attitude control of quadrotors based on fractional sliding modes: Theory and experiments. IET Control Theory Appl. 10(7), 825–832 (2016)
Muñoz, F., González-Hernández, I., Salazar, S., Espinoza, E.S., Lozano, R.: Second order sliding mode controllers for altitude control of a quadrotor UAS: Real-time implementation in outdoor environments. Neurocomputing 233(2016), 61–71 (2017)
Labbadi, M., Cherkaoui, M.: Novel robust super twisting integral sliding mode controller for a quadrotor under external disturbances. International Journal of Dynamics and Control (Dec. 2019)
Aguilar-Ibáñez, C., Sira-Ramírez, H., Suárez-Castañón, M.S., Martínez-Navarro, E., Moreno-Armendariz, M.A.: The trajectory tracking problem for an unmanned four-rotor system: Flatness-based approach. Int. J. Control 85(1), 69–77 (2012)
Chamseddine, A., Zhang, Y., Rabbath, C.A., Join, C., Theilliol, D.: Flatness-based trajectory planning/replanning for a quadrotor unmanned aerial vehicle. IEEE Trans. Aerosp. Electron. Syst. 48 (4), 2832–2848 (2012)
Wang, N., Deng, Q., Xie, G., Pan, X.: Hybrid finite-time trajectory tracking control of a quadrotor. ISA Trans (2019)
Wang, X., Shirinzadeh, B.: Nonlinear multiple integrator and application to aircraft navigation. IEEE Trans. Aerosp. Electron. Syst. 50(1), 607–622 (2014)
Yang, H., Cheng, L., Xia, Y., Yuan, Y.: Active disturbance rejection attitude control for a dual Closed-Loop quadrotor under gust wind. IEEE Trans. Control Syst. Technol. 26(4), 1400–1405 (2018)
Shah, P., Agashe, S.: Review of fractional PID controller. Mechatronics 38, 29–41 (2016). https://doi.org/10.1016/j.mechatronics.2016.06.005
Wang, J., Shao, C., Chen, Y.Q. : Fractional order sliding mode control via disturbance observer for a class of fractional order systems with mismatched disturbance. Mechatronics 53, 8–19 (2018). https://doi.org/10.1016/j.mechatronics.2018.05.006
Nojavanzadeh, D., Badamchizadeh, M.: Adaptive fractional-order non-singular fast terminal sliding mode control for robot manipulators. IET Control Theory Appl. 10(13), 1565–1572 (2016)
Yaoyao, W., Surong, J., Bai, C., Hongtao, W.: Advances in Engineering Software A new continuous fractional-order nonsingular terminal sliding mode control for cable-driven manipulators. Advances in Engineering Software 119(2017), 21–29 (2018)
Wang, Y., Yan, F., Chen, B., et al.: Adaptive super-twisting fractional-order nonsingular terminal sliding mode control of cable-driven manipulators. ISA Trans 86, 163–180 (2018). https://doi.org/10.1016/j.isatra.2018.11.009
Chen, S.Y., Chiang, H.H., Liu, T.S. , Chang, C.H.: Precision motion control of permanent magnet linear synchronous motors using adaptive fuzzy fractional-order sliding-mode control. IEEE/ASME Trans Mechatronics 24, 741–752 (2019). https://doi.org/10.1109/TMECH.2019.2892401
Fayazi, A., Pariz, N., Karimpour, A., Hosseinnia, S.H.: Robust position-based impedance control of lightweight single-link flexible robots interacting with the unknown environment via a fractional-order sliding mode controller. Robotica 36, 1920–1942 (2018). https://doi.org/10.1017/S0263574718000802
Raffo, G.V., Ortega, M.G., Rubio, F.R.: An Integral predictive / nonlinear \(h_{\infty }\) control structure for a quadrotor. Automatica 46(1), 29–39 (2010)
Ayad, R., Nouibat, W., Zareb, M., Bestaoui Sebanne, Y.: Full control of quadrotor aerial robot using Fractional-Order FOPID. Iran. J. Sci. Technol. Trans. Electr. Eng. 4, 2013 (2018)
Izaguirre-Espinosa, C., Muñoz-Vazquez, A. J., Sanchez-Orta, A., Parra-Vega, V., Fantoni, I.: Fractional-Order Control for robust Position/Yaw tracking of quadrotors with experiments. IEEE Trans. Control Syst. Technol., pp 1–6 (2018)
Mehmet, O.: Battery power loss compensated fractional order. Asian J. Control 14(2), 413–425 (2012)
Li, Z., Ma, X., Li, Y.: Robust tracking control strategy for a quadrotor using RPD-SMC and RISE. Neurocomputing 331, 312–322 (2018)
Liu, H., Li, D., Zuo, Z., Zhong, Y.: Robust three-loop trajectory tracking control for quadrotors with multiple uncertainties. IEEE Trans. Ind. Electron. 63(4), 2263–2274 (2016)
Ailon, Arogeti, S.: Closed-form nonlinear tracking controllers for quadrotors with model and input generator uncertainties. Automatica 54, 317–324 (2015)
Cabecinhas, D., Naldi, R., Silvestre, C., Cunha, R., Marconi, L.: Robust Landing and Sliding Maneuver Hybrid Controller for a Quadrotor Vehicle. pp 1–13 (2015)
Vahdanipour, M., Khodabandeh, M.: Adaptive fractional order sliding mode control for a quadrotor with a varying load. Aerosp. Sci. Technol. 86, 737–747 (2019)
Rios, H., Falcon, R., Gonzalez, O.A., Dzul, A.: Continuous Sliding-Mode control strategies for quadrotor robust tracking: Real-Time application. IEEE Trans. Ind. Electron. 66(2), 1264–1272 (2019)
Ai, X., Yu, J.: Flatness-based finite-time leader-follower formation control of multiple quadrotors with external disturbances. Aerosp. Sci. Technol. 92, 20–33 (2019)
Eskandarpour, A., Sharf, I.: A constrained error-based MPC for path following of quadrotor with stability analysis. Nonlinear Dyn (2019)
Shi, X., Cheng, Y., Yin, C., Dadras, S., Huang, X.: Design Of Fractional-Order backstepping sliding mode control for quadrotor UAV. Asian J. Control 21(1), 156–171 (2018)
Izaguirre-espinosa, A., Muñoz-vázquez, A.J., Sánchez-orta, A., Parra-vega, V.: Fractional attitude-reactive control for robust quadrotor position stabilization without resolving underactuation. Control Eng. Pract. 53, 47–56 (2016)
Liu, H., Zhao, W., Zuo, Z., Zhong, Y.: Robust control for quadrotors with multiple Time-Varying uncertainties and delays. IEEE Trans. Ind. Electron. 64(2), 1303–1312 (2017)
Wang, C.C.H.K., You, J.C.X.: Tracking differentiator and extended state observer-based nonsingular fast terminal sliding mode attitude control for a quadrotor. Nonlinear Dyn. (2018)
Efe, M.Ö.: Neural network assisted computationally simple PIλdμ control of a quadrotor UAV. IEEE Trans. Ind. Informatics 7(2), 354–361 (2011)
Xu, Z., Nian, X., Wang, H., Chen, Y.: Robust guaranteed cost tracking control of quadrotor UAV with uncertainties. ISA Trans. 69, 157–165 (2017)
Cai, W., She, J., Wu, M., Ohyama, Y.: Disturbance suppression for quadrotor UAV using sliding-mode-observer-based equivalent-input-disturbance approach. ISA Trans. (2019)
Zhang, J., Ren, Z., Deng, C., Wen, B.: Adaptive fuzzy global sliding mode control for trajectory tracking of quadrotor UAVs. Nonlinear Dyn. (2019)
Chen, F., Lei, W., Zhang, K., Tao, G., Jiang, B.: A novel nonlinear resilient control for a quadrotor UAV via backstepping control and nonlinear disturbance observer. Nonlinear Dyn. 85(2), 1281–1295 (2016)
Razmi, H., Afshinfar, S.: Neural network-based adaptive sliding mode control design for position and attitude control of a quadrotor UAV. Aerosp. Sci. Technol. 91, 12–27 (2019)
Casta, H., Gordillo, J.L.: Spatial modeling and robust flight control based on adaptive sliding mode approach for a quadrotor MAV (2018)
Shi, X., Cheng, Y., Yin, et al.: Design of fractional-order backstepping sliding mode control for quadrotor UAV. Asian J Control 21, 156–171 (2019). https://doi.org/10.1002/asjc.1946
Bouzid, Y., Siguerdidjane, H., Bestaoui, Y.: Nonlinear internal model control applied to VTOL multi-rotors UAV. Mechatronics 47, 49–66 (2017)
Podlubny, I.: Fractional Differential Equations. New York: academic (1999)
Das, S.: Functional Fractional Calculus for System Identification and Controls. Springer, Heidelberg (2008)
Mu, C., Zhang, Y.: Learning-based robust tracking control of quadrotor with time-varying and coupling uncertainties. IEEE Trans Neural Networks Learn Syst, pp 1–15. https://doi.org/10.1109/tnnls.2019.2900510 (2019)
Labbadi, M., Cherkaoui, M., El Houm, Y., Guisser, M.: A comparative analysis of control strategies for stabilizing a quadrotor. In: International Conference Europe Middle East, North Africa Information Systems and Technologies to Support Learning. https://doi.org/10.1007/978-3-030-03577-8 (2019)
Labbadi, M., Cherkaoui, M., El houm, Y., Guisser, M.: Modeling and robust integral sliding mode control for a quadrotor unmanned aerial vehicle. In: 2018 6th Int. Renew. Sustain. Energy Conf., pp. 1–6 (2018)
Labbadi, M., Cherkaoui, M.: Robust adaptive backstepping fast terminal sliding mode controller for uncertain quadrotor UAV. Aerosp. Sci. Technol. 1, 105306 (2019)
Labbadi, M., Cherkaoui, M.: Robust integral terminal sliding mode control for quadrotor UAV with external disturbances. International Journal of Aerospace Engineering 2019, 1–10 (2019)
Yin, C., Chen, Y., Zhong, S.M.: Fractional-order sliding mode based extremum seeking control of a class of nonlinear systems. Automatica 50(12), 3173–3181 (2014)
Freire, F.P., Martins, N.A., Splendor, F.: A simple optimization method for tuning the gains of PID controllers for the autopilot of Cessna 182 aircraft using model-in-the-loop platform. J. Control Autom. Electr. Syst. 29, 441–450 (2018). https://doi.org/10.1007/s40313-018-0391-x
Tepljakov, A., Petlenkov, E., Belikov, J.: FOMCON: Fractional-order Modeling and control toolbox for MATLAB. In: Proc. 18th Int. Conf. Mixed Des. Integr. Circuits Syst., pp. 684–689 (2011)
Derafa, L., Benallegue, A., Fridman, L.: Super twisting control algorithm for the attitude tracking of a four rotors UAV. J. Franklin Inst. 349, 685–699 (2012). https://doi.org/10.1016/j.jfranklin.2011.10.011
Alejandro, D., Moreno, J.A., Fridman, L.: Reaching time estimation for super-twisting based on Lyapunov function. In: IEEE Conf Decis Control pp 0–6, (2009)
Labbadi, M., Cherkaoui, M.: Robust adaptive nonsingular fast terminal sliding-mode tracking control for an uncertain quadrotor UAV subjected to disturbances. ISA Trans. 99, 290–304 (2020)
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interests
We have no conflict of interest to declare.
Additional information
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Appendix
Appendix
The Super-Twisting Algorithm (STA) with a perturbation is defined by the following equation as [66, 67].
Proof
To proof the stability of the system, the standard Super-Twisting Algorithm (STA) with a perturbation is defined as [66, 67]:
The term \({\Upsilon }_{1} \in \mathbb {R}\) and \({\Upsilon }_{2}\in \mathbb {R}\) denote the state variables, \(b_{1}\in \mathbb {R^{+}}\), \(b_{2}\in \mathbb {R^{+}}\) and d(t, ϒ) is a perturbation term bounded as (d(t,ϒ) < D). Define the Lyapunov function presented in [66, 67] as
with \(\zeta =[\vert {\Upsilon }_{1} \vert ^{\frac {1}{2}}sign({\Upsilon }_{1}),{\Upsilon }_{2}]\) and P = PT is a non-negative matrix, which is a solution of an algebraic Lyapunov equation defined in Eq. 54.
with \(Q_{ST}=Q_{ST}^{T}>0\) and AST is Hurwitz, define in Eq. 55
Moroever, the derivative of \(\dot {V}\) respect to time presented in [66, 67] satisfies the
where
is a scalar depending on the selection of the matrix QST. □
Rights and permissions
About this article
Cite this article
Labbadi, M., Boukal, Y. & Cherkaoui, M. Path Following Control of Quadrotor UAV With Continuous Fractional-Order Super Twisting Sliding Mode. J Intell Robot Syst 100, 1429–1451 (2020). https://doi.org/10.1007/s10846-020-01256-3
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10846-020-01256-3