Abstract
This paper presents a robust altitude control that merges the principles of active disturbance rejection control (ADRC) with the in-ground-effect model (IGE). To this end, a nonlinear extended state observer is designed along the vertical axis, taking attitude and altitude measurements. Then, the forces generated by low-level flight, ground effect and other external disturbances are estimated and used (as an anticipation term) together with a non-linear control law (as a feedback term) to reject them. Closed-loop stability is analyzed in the Lyapunov sense. Extensive numerical simulations and real-time experiments validate the proposal. Thanks to its simplicity, the control algorithm is easy to implement. It can be used for various maneuvers that depend on proximity to the ground, obstacles or surfaces, such as take-off, landing, inspection, surveillance and hovering.
Similar content being viewed by others
Data Availability
The data sets generated and analyzed during the current study are available from the corresponding author on reasonable request.
References
He, T., Zeng, Y., Hu, Z.: Research of multi-rotor uavs detailed autonomous inspection technology of transmission lines based on route planning. IEEE Access 7, 114955–114965 (2019). https://doi.org/10.1109/ACCESS.2019.2935551
Chung, H.-M., Maharjan, S., Zhang, Y., Eliassen, F., Strunz, K.: Placement and routing optimization for automated inspection with unmanned aerial vehicles: A study in offshore wind farm. IEEE Transactions on Industrial Informatics 17(5), 3032–3043 (2021). https://doi.org/10.1109/TII.2020.3004816
Sawadsitang, S., Niyato, D., Tan, P.-S., Wang, P.: Joint ground and aerial package delivery services: A stochastic optimization approach. IEEE Trans. Intell. Transp. Syst. 20(6), 2241–2254 (2019). https://doi.org/10.1109/TITS.2018.2865893
Tokekar, P., Hook, J.V., Mulla, D., Isler, V.: Sensor planning for a symbiotic uav and ugv system for precision agriculture. IEEE Trans. Robot. 32(6), 1498–1511 (2016). https://doi.org/10.1109/TRO.2016.2603528
Reddy Maddikunta, P.K., Hakak, S., Alazab, M., Bhattacharya, S., Gadekallu, T.R., Khan, W.Z., Pham, Q.-V.: Unmanned aerial vehicles in smart agriculture: Applications, requirements, and challenges. IEEE Sensors J. 21(16), 17608–17619 (2021). https://doi.org/10.1109/JSEN.2021.3049471
Zhang, S., Xue, X., Chen, C., Sun, Z., Sun, T.: Development of a low-cost quadrotor uav based on adrc for agricultural remote sensing. International Journal of Agricultural and Biological Engineering 12, 82–87 (2019). https://doi.org/10.25165/j.ijabe.20191204.4641
Chhikara, P., Tekchandani, R., Kumar, N., Guizani, M., Hassan, M.M.: Federated learning and autonomous uavs for hazardous zone detection and aqi prediction in iot environment. IEEE Internet of Things Journal 8(20), 15456–15467 (2021). https://doi.org/10.1109/JIOT.2021.3074523
Lu, Y., Macias, D., Dean, Z.S., Kreger, N.R., Wong*, P.K.: A uavmounted whole cell biosensor system for environmental monitoring applications. IEEE Transactions on NanoBioscience 14(8), 811–817 (2015). https://doi.org/10.1109/TNB.2015.2478481
Sambolek, S., Ivasic-Kos, M.: Automatic person detection in search and rescue operations using deep cnn detectors. IEEE Access 9, 37905–37922 (2021). https://doi.org/10.1109/ACCESS.2021.3063681
Dousai, N.M.K., Lončarić, S.: Detecting humans in search and rescue operations based on ensemble learning. IEEE Access 10, 26481–26492 (2022). https://doi.org/10.1109/ACCESS.2022.3156903
Nascimento, T.P., Saska, M.: Position and attitude control of multi-rotor aerial vehicles: A survey. Annu. Rev. Control. 48, 129–146 (2019). https://doi.org/10.1016/j.arcontrol.2019.08.004
Abdelmaksoud, S.I., Mailah, M., Abdallah, A.M.: Control strategies and novel techniques for autonomous rotorcraft unmanned aerial vehicles: A review. IEEE Access 8, 195142–195169 (2020). https://doi.org/10.1109/ACCESS.2020.3031326
González-Guerrero, J.C., Díaz-Téllez, J., Estevez-Carreon, J., Mendoza-Vazquez, R., Meraz-Melo, M.A., Guerrero-Castellanos, J.F.: Low altitude control of the vtol uav tolerant to ground effect and actuator failures. In: 2022 International conference on unmanned aircraft systems (ICUAS), pp. 1504–1509 (2022). https://doi.org/10.1109/ICUAS54217.2022.9836161
Cheeseman, I.C., D, P., Bennett, W.E., D, P., Bennett, W.E.: The effect of ground on a helicopter rotor in forward flight. Tech. Rep. (1955)
Hayden, J.S.: The effect of the ground on helicopter hovering power required. (1976)
Danjun, L., Yan, Z., Zongying, S., Geng, L.: Autonomous landing of quadrotor based on ground effect modelling. In: 2015 34th Chinese control conference (CCC), pp. 5647–5652 (2015). https://doi.org/10.1109/ChiCC.2015.7260521
Kan, X., Thomas, J., Teng, H., Tanner, H.G., Kumar, V., Karydis, K.: Analysis of ground effect for small-scale uavs in forward flight. IEEE Robotics and Automation Letters 4(4), 3860–3867 (2019). https://doi.org/10.1109/LRA.2019.2929993
Sharf, I., Nahon, M., Harmat, A., Khan, W., Michini, M., Speal, N., Trentini, M., Tsadok, T., Wang, T.: Ground effect experiments and model validation with draganflyer x8 rotorcraft. In: 2014 International conference on unmanned aircraft systems (ICUAS), pp. 1158–1166 (2014). https://doi.org/10.1109/ICUAS.2014.6842370
Ryan, T.: Modelling of quadrotor ground effect forces via simple visual feedback and support vector regression. (2012). https://doi.org/10.2514/6.2012-4833
Davis, E., Pounds, P.E.I.: Passive position control of a quadrotor with ground effect interaction. IEEE Robotics and Automation Letters 1(1), 539–545 (2016). https://doi.org/10.1109/LRA.2016.2514351
Anh, T.H., Binh, N.T., Song, J.W.: In-ground-effect model based adaptive altitude control of rotorcraft unmanned aerial vehicles. IEEE Robotics and Automation Letters 7(2), 794–801 (2022). https://doi.org/10.1109/LRA.2021.3133932
Castillo, P., Dzul, A., Lozano, R.: Real-time stabilization and tracking of a four-rotor mini rotorcraft. IEEE Trans. Control. Syst. Technol. 12(4), 510–516 (2004). https://doi.org/10.1109/TCST.2004.825052
Lee, T., Leok, M., McClamroch, N.H.: Geometric tracking control of a quadrotor uav on se(3). In: 49th IEEE Conference on decision and control (CDC), pp. 5420–5425 (2010). https://doi.org/10.1109/CDC.2010.5717652
González, I., Salazar, S., Lozano, R.: Chattering-free sliding mode altitude control for a quad-rotor aircraft: Real-time application. In: Journal of intelligent & robotic systems, pp. 137–155 (2014). https://doi.org/10.1007/s10846-013-9913-8
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, 61–71 (2017). https://doi.org/10.1016/j.neucom.2016.08.111. SI: CCE 2015
Xuan Mung, N., Hong, S.-K.: Improved altitude control algorithm for quadcopter unmanned aerial vehicles. Appl. Sci. 9 (2019). https://doi.org/10.3390/app9102122
Ahmed, N., Raza, A., Shah, S.A.A., Khan, R.: Robust compositedisturbance observer based flight control of quadrotor attitude. J. Intell. Robot. Syst. 103(1) (2021). https://doi.org/10.1007/s10846-021-01463-6
Younes, Y., Drak, A., Noura, H., Rabhi, A., El hajjaji, A.: Robust modelfree control applied to a quadrotor uav. J. Intell. Robot. Syst. 84 (2016). https://doi.org/10.1007/s10846-016-0351-2
Kothari, M., Postlethwaite, I., Gu, D.-W.: Uav path following in windy urban environments. J. Intell. Robot. Syst. 74, 1013–1028 (2013). https://doi.org/10.1007/s10846-013-9873-z
Madruga, S.P., Tavares, A.H.B.M., Luiz, S.O.D., do Nascimento, T.P., Lima, A.M.N.: Aerodynamic effects compensation on multi-rotor uavs based on a neural network control allocation approach. IEEE/CAA J. Auto. Sin. 9(2), 295–312 (2022). https://doi.org/10.1109/JAS.2021.1004266
Hedjar, R., Al Zuair, M.A.: Robust altitude stabilization of vtol-uav for payloads delivery. IEEE Access 7, 73583–73592 (2019). https://doi.org/10.1109/ACCESS.2019.2919701
Kazim, M., Azar, A.T., Koubaa, A., Zaidi, A.: Disturbance-rejectionbased optimized robust adaptive controllers for uavs. IEEE Syst. J. 15(2), 3097–3108 (2021). https://doi.org/10.1109/JSYST.2020.3006059
Cabecinhas, D., Cunha, R., Silvestre, C.: A globally stabilizing path following controller for rotorcraft with wind disturbance rejection. IEEE Trans. Control Syst. Technol. 23(2), 708–714 (2015). https://doi.org/10.1109/TCST.2014.2326820
Azid, S.I., Kumar, K., Cirrincione, M., Fagiolini, A.: Robust motion control of nonlinear quadrotor model with wind disturbance observer. IEEE Access 9, 149164–149175 (2021). https://doi.org/10.1109/ACCESS.2021.3124609
Asignacion, A., Suzuki, S., Noda, R., Nakata, T., Liu, H.: Frequencybased wind gust estimation for quadrotors using a nonlinear disturbance observer. IEEE Robot. Auto. Lett. 7(4), 9224–9231 (2022). https://doi.org/10.1109/LRA.2022.3190073
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. Neurocomput. 233, 61–71 (2017). https://doi.org/10.1016/j.neucom.2016.08.111. SI: CCE 2015
Shtessel, Y., Edwards, C., Fridman, L., Levant, A.: Sliding mode control and observation. Birkhäuser New York, NY, ??? (2014)
Chen, Y., Zhang, G., Zhuang, Y., Hu, H.: Autonomous flight control for multi-rotor uavs flying at low altitude. IEEE Access 7, 42614–42625 (2019). https://doi.org/10.1109/ACCESS.2019.2908205
Guo, K., Zhang, W., Zhu, Y., Jia, J., Yu, X., Zhang, Y.: Safety control for quadrotor uav against ground effect and blade damage. IEEE Trans. Ind. Electron. 69(12), 13373–13383 (2022). https://doi.org/10.1109/TIE.2022.3140494
He, X., Kou, G., Calaf, M., Leang, K.: In-ground-effect modeling and nonlinear disturbance observer for multi-rotor uav control. J. Dyn. Syst. Meas. Control 141 (2019). https://doi.org/10.1115/1.4043221
Han, J.: From PID to active disturbance rejection control. IEEE Trans. Ind. Electron. 56(3), 900–906 (2009)
Chan, L., Naghdy, F., Stirling, D.: Extended active observer for force estimation and disturbance rejection of robotic manipulators. Robot. Auton. Syst. 61(12), 1277–1287 (2013)
Xue, W., Huang, Y., Gao, Z.: On adrc for non-minimum phase systems: canonical form selection and stability conditions. Control Theory and Technol 14(3), 199–208 (2016)
Mehdi, H., Boubaker, O.: Robust impedance control-based lyapunov-hamiltonian approach for constrained robots. Int. J. Adv. Robot. Syst. 12(12), 190 (2015)
Yu, Y., Yang, Z., Han, C., Liu, H.: Disturbance-observer based control for magnetically suspended wheel with synchronous noise. Control Eng. Pract. 72, 83–89 (2018)
Sira-Ramirez, H., Luviano-Juárez, A., Ramirez-Neria, M., Zurita- Bustamante, E.: Active Disturbance Rejection Control of Dynamic Systems: A Flatness Based Approach, (2018)
Guo, L., Cao, S.: Anti-disturbance control theory for systems with multiple disturbances: A survey. ISA Trans. 53(4), 846–849 (2014). https://doi.org/10.1016/j.isatra.2013.10.005. Disturbance Estimation and Mitigation
Chang, K., Xia, Y., Huang, K., Ma, D.: Obstacle avoidance and active disturbance rejection control for a quadrotor. Neurocomputing 190, 60–69 (2016). https://doi.org/10.1016/j.neucom.2016.01.033
Dong, W., Gu, G.-Y., 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). https://doi.org/10.1016/j.robot.2016.05.005
Abadi, A., Amraoui, A.E., Mekki, H., Ramdani, N.: Robust tracking control of quadrotor based on flatness and active disturbance rejection control. IET Control Theory & Applications 14(8), 1057–1068 (2020). https://doi.org/10.1049/iet-cta.2019.1363
Najm, A.A., Ibraheem, I.K.: Altitude and attitude stabilization of uav quadrotor system using improved active disturbance rejection control. Arab. J. Sci. Eng. 45(3), 1985–1999 (2020). https://doi.org/10.1007/s13369-020-04355-3
Cheng, Y., Dai, L., Li, A., Yuan, Y., Chen, Z.: Active disturbance rejection generalized predictive control of a quadrotor uav via quantitative feedback theory. IEEE Access 10, 37912–37923 (2022). https://doi.org/10.1109/ACCESS.2022.3165093
Zhang, Y., Chen, Z., Sun, M., Zhang, X.: Trajectory tracking control of a quadrotor uav based on sliding mode active disturbance rejection control. Nonlinear Analysis: Modelling and Control 24(4), 545–560 (2019). https://doi.org/10.15388/NA.2019.4.4
Nie, Z.-Y., Zhang, B., Wang, Q.-G., Liu, R.-J., Luo, J.-L.: Adaptive active disturbance rejection control guaranteeing uniformly ultimate boundedness and simplicity. International Journal of Robust and Nonlinear Control 30(17), 7278–7294 (2020). https://doi.org/10.1002/rnc.5177
Guerrero-Castellanos, J.F., Rifaï, H., Arnez-Paniagua, V., Linares-Flores, J., Saynes-Torres, L., Mohammed, S.: Robust active disturbance rejection control via control lyapunov functions: Application to actuatedankle-foot-orthosis. Control Eng. Pract. 80, 49–60 (2018)
Guerrero-Castellanos, J.F., Marchand, N., Hably, A., Lesecq, S., Delamare, J.: Bounded attitude control of rigid bodies: Real-time experimentation to a quadrotor mini-helicopter. Control Eng. Pract. 19(8), 790–797 (2011). https://doi.org/10.1016/j.conengprac.2011.04.004
Tomić, T., Haddadin, S.: Simultaneous estimation of aerodynamic and contact forces in flying robots: Applications to metric wind estimation and collision detection. In: 2015 IEEE International conference on robotics and automation (ICRA), pp. 5290–5296 (2015). https://doi.org/10.1109/ICRA.2015.7139937
Acknowledgements
J. Díaz-Téllez thanks the National Council of Science and Technology, Mexico (CONACYT) for providing financial support through his Ph. D. scholarship.
Funding
This work is part of the French-Mexican TOBACCO project funded by the FORDECYT-PRONACES through the joint SEP-CONACYT-ANUIES-ECOS Nord program (MX-296702 & FR-M18M02).
Author information
Authors and Affiliations
Contributions
Conceptualization: J. Díaz-Téllez and J.F. Guerrero-Castellanos; Methodology: J.F. Guerrero-Castellanos, N. Marchand and S. Durand; Software and analysis: J. Díaz-Téllez and F. Pouthier; Writing - original draft preparation: J. Díaz-Téllez and J.F. Guerrero-Castellanos; Writing - review and editing: N. Marchand, F. Pouthier, S. Durand.
Corresponding author
Ethics declarations
Ethics Approval
Research does not involve Human Participants and/ or Animals.
Consent to participate
Not applicable.
Consent to publish
Not applicable.
Conflicts of interest
The authors declare no conflict of interest.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Díaz-Téllez, J., Guerrero-Castellanos, J.F., Pouthier, F. et al. In-Ground-Effect Disturbance-Rejection Altitude Control for Multi-Rotor UAVs. J Intell Robot Syst 109, 27 (2023). https://doi.org/10.1007/s10846-023-01958-4
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s10846-023-01958-4