Abstract
In this paper, a mass adaptive control method combining with robust sliding mode control (SMC) and linear active disturbance rejection control (LADRC) is designed for the quadrotor load unmanned aerial vehicle (UAV) with mass variation. In detail, firstly, the mass variation in the quadrotor affects the position of its centroid, taking into account the changes of centroid position, which makes the established model more accurate. Moreover, a mass adaptive law is designed to eliminate the influence of mass variation. Secondly, SMC can enhance the robustness of the controller, improve the anti-disturbance performance and overcome the problem of low control precision caused by bandwidth limitation of LADRC. The linear extended state observer estimates the external disturbances of the system and the internal unmodeled dynamics caused by the SMC chattering in real time, and then, the total disturbance is compensated by the proportional–derivative controller. The proposed scheme combines the advantages of SMC and LADRC and complements each other. Thirdly, in order to simplify the parameter setting, the adaptive control is introduced in LADRC to adjust the controller parameters in real time, which is beneficial to the stability analysis of the control system. Then Lyapunov stability theory is used to prove the stability of the whole system. Finally, the simulation is compared with LADRC and dynamic surface active disturbance rejection control. The results show that the designed scheme has smaller overshoot and faster response speed, which proves its superiority. Moreover, the designed adaptive law is also effective, it can eliminate the influence of parameter deviation, so that the proposed scheme can track the reference signal stably even in the presence of disturbances.
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References
Zhang, J., Ren, Z., Deng, C., Wen, B.: Adaptive fuzzy global sliding mode control for trajectory tracking of quadrotor UAVs. Nonlinear Dyn. 97(1), 609–627 (2019)
Zou, Y., Zhu, B.: Adaptive trajectory tracking controller for quadrotor systems subject to parametric uncertainties. J. Franklin Inst. 354(15), 6724–6746 (2017)
Ramirez-Rodriguez, H., Parra-Vega, V., Sanchez-Orta, A., Garcia-Salazar, O.: Robust backstepping control based on integral sliding modes for tracking of quadrotors. J. Intell. Rob. Syst. 73, 51–66 (2014)
Mc, A., Lta, B.: Robust PID control of quadrotors with power reduction analysis. ISA Trans. 98, 47–62 (2020)
Najm, A.A., Ibraheem, I.K.: Nonlinear PID controller design for a 6-DOF UAV quadrotor system. Eng. Sci. Technol. Int. J. 22(4), 1087–1097 (2019)
Outeiro, P., Cardeira, C., Oliveira, P.: Multiple-model adaptive control architecture for a quadrotor with constant unknown mass and inertia. Aerosp Sci Technol 117, 106899 (2021)
Chen, L., Liu, Z., Gao, H., Wang, G.: Robust adaptive recursive sliding mode attitude control for a quadrotor with unknown disturbances. ISA Trans. (2021). https://doi.org/10.1016/j.isatra.2021.04.046
Hamid, G., Maedeh, E., Hamed, K.: Adaptive super-twisting non-singular terminal sliding mode control for tracking of quadrotor with bounded disturbances. Aerosp. Sci. Technol. 112(1), 106616 (2021)
Labbadi, M., Boukal, Y., Cherkaoui, M., Djemal, M.: Fractional-order global sliding mode controller for an uncertain quadrotor UAVs subjected to external disturbances. J. Franklin Inst. 358(9), 4822–4847 (2021)
Zhang, Z., Chen, T., Zheng, L.: A multilayer neural dynamic controller design method of quadrotor UAV for completing time-varying tasks. Nonlinear Dyn. 104(4), 3597–3616 (2021)
Han, J.Q.: From PID to active disturbance rejection control. IEEE Trans. Industr. Electron. 56(3), 900–906 (2009)
Chang, K., Xia, Y., Huang, K., Ma, D.: Obstacle avoidance and active disturbance rejection control for a quadrotor. Neurocomputing 19, 60–69 (2016)
Bouzid, Y., Siguerdidjane, H., Guiatni, M., Lamraoui, H.C.: Reinforcement of a reference model-based control using active disturbance rejection principle: application to quadrotor. IFAC-PapersOnLine. 52(12), 152–157 (2019)
Wei, D., Gu, G., Zhu, X., Ding, H.: A high-performance flight control approach for quadrotors using a modified active disturbance rejection technique. Robot. Auton. Syst. 83, 177–187 (2016)
Zhang, Y., Chen, Z., Sun, M.: Trajectory tracking control for a quadrotor unmanned aerial vehicle based on dynamic surface active disturbance rejection control. Trans. Inst. Meas. Control. 42(12), 2198–2205 (2020)
Luo, S., Sun, Q., Sun, M., Tan, P., Wu, W., Sun, H., Chen, Z.: On decoupling trajectory tracking control of unmanned powered parafoil using ADRC-based coupling analysis and dynamic feedforward compensation. Nonlinear Dyn. 92(4), 1619–1635 (2018)
Zhu, E., Pang, J., Sun, N., Gao, H., Sun, Q., Chen, Z.: Airship horizontal trajectory tracking control based on active disturbance rejection control. Nonlinear Dyn. 75(4), 725–734 (2014)
Gao, Z.: Scaling and bandwidth-parameterization based controller tuning. In: Proceedings of the 2003 American Control Conference, Denver, CO, USA, pp. 4989–4996 (2003)
Zhang, Y., Chen, Z., Zhang, X., Sun, Q., Sun, M.: A novel control scheme for quadrotor UAV based upon active disturbance rejection control. Aerosp. Sci. Technol. 79, 601–609 (2018)
Guo, B., Bacha, S., Alamir, M., Mohamed, A., Boudinet, C.: LADRC applied to variable speed micro-hydro plants: experimental validation. Control. Eng. Pract. 85, 290–298 (2019)
Wang, Y., Tan, W., Cui, W., Han, W., Guo, Q.: Linear active disturbance rejection control for oscillatory systems with large time-delays. J. Franklin Inst. 358, 6240–6260 (2021)
Hou, G., Gong, L., Wang, M., Yu, X., Yang, Z., Mou, X.: A novel linear active disturbance rejection controller for main steam temperature control based on the simultaneous heat transfer search. ISA Trans. (2021). https://doi.org/10.1016/j.isatra.2021.05.003
Wu, J., Peng, H., Chen, Q., Peng, X.: Modeling and control approach to a distinctive quadrotor helicopter. ISA Trans. 53(1), 173–185 (2014)
Cai, Z., Lou, J., Zhao, J., Wu, K., Liu, N., Wang, Y.: Quadrotor trajectory tracking and obstacle avoidance by chaotic grey wolf optimization-based active disturbance rejection control. Mech. Syst. Signal Process. 128, 636–654 (2019)
Zhao, Z., Cao, D., Yang, J., Wang, H.: High-order sliding mode observer-based trajectory tracking control for a quadrotor UAV with uncertain dynamics. Nonlinear Dyn. 102(4), 2583–2596 (2020)
Eskandarpour, A., Sharf, I.: A constrained error-based MPC for path following of quadrotor with stability analysis. Nonlinear Dyn. 99(2), 899–918 (2020)
Tang, P., Lin, D., Zheng, D., Fan, S., Ye, J.: Observer based finite-time fault tolerant quadrotor attitude control with actuator faults. Aerosp. Sci. Technol. 104, 105968 (2020)
Hua, C., Wang, K., Chen, J., You, X.: Tracking differentiator and extended state observer-based nonsingular fast terminal sliding mode attitude control for a quadrotor. Nonlinear Dyn. 94(1), 343–354 (2018)
Nekoukar, V., Dehkordi, N.: Robust path tracking of a quadrotor using adaptive fuzzy terminal sliding mode control. Control Eng. Pract. 110, 104763 (2021)
Altan, A.: Performance of metaheuristic optimization algorithms based on swarm intelligence in attitude and altitude control of unmanned aerial vehicle for path following. In: 4th International Symposium on Multidisciplinary Studies and Innovative Technologies, Turkey, 22–24 Oct, pp.1–6 (2020)
Wang, B., Yu, X., Mu, L., Zhang, Y.: Disturbance observer-based adaptive fault-tolerant control for a quadrotor helicopter subject to parametric uncertainties and external disturbances. Mech. Syst. Signal Process. 120, 727–743 (2019)
Nguyen, S.D., Lam, B.D., Ngo, V.H.: Fractional-order sliding-mode controller for semi-active vehicle MRD suspensions. Nonlinear Dyn. 101(2), 795–821 (2020)
Liu, W., Zhao, T.: An active disturbance rejection control for hysteresis compensation based on neural networks adaptive control. ISA Trans. 109, 81–88 (2021)
Hovakimyan, N., Nardi, F., Calise, A., Kim, N.: Adaptive output feedback control of uncertain nonlinear systems using single-hidden-layer neural networks. IEEE Trans. Neural Netw. 13(6), 1420–1431 (2002)
Zhao, T., Tan, Y.: Adaptive H∞ RBFN tracking control for nonlinear systems with unknown hysteresis. In: IEEE International Symposium on Intelligent Control, Taipei, Taiwan, 2–4 Sep, pp. 352–356. IEEE (2004)
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Wang, Z., Zhao, T. Based on robust sliding mode and linear active disturbance rejection control for attitude of quadrotor load UAV. Nonlinear Dyn 108, 3485–3503 (2022). https://doi.org/10.1007/s11071-022-07349-y
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DOI: https://doi.org/10.1007/s11071-022-07349-y