Synthesis of Combined Quadrocopter Attitude and Altitude Control Based on Block Approach with Sigmoidal Feedbacks
Keywords:
UAV, external disturbances, combined control, block approach, hyperbolic tangentAbstract
This paper considers the problem of controlling the attitude and altitude of a quadrocopter in the presence of uncertainties in the plant model. When solving this problem, it is especially important to consider the peculiarities of the plant: strong susceptibility to roll, pitch, and altitude oscillations due to the quadrocopter design and motor dynamics (with yaw being the least susceptible to oscillations due to motor dynamics compared with other controllable variables). To achieve high control quality in the presence of uncertainties, combined control is usually applied. It is constructed as a sum of two parts: a basic stabilizing part and a part compensating uncertainties with the help of a disturbance observer. Typically, both parts contain linear feedback. However, when the output variables of the plant track non-smooth reference signals, linear feedback can cause overshooting and increased oscillations. To prevent these problems, we propose a combined control law with smooth and bounded feedback in the form of the hyperbolic tangent. This feedback is used by both the controller and the disturbance observer. In this case, the control synthesis is based on the structural properties of the plant using the block approach. Its application provided invariance of the output variables with respect to not only matched but also unmatched uncertainties, and also allowed to construct a disturbance observer of the minimum possible order. In addition, to reduce the oscillations, a part with plant accelerations was introduced into the control law. To realize the proposed approach, it is sufficient to know the nominal values of some parameters of the plant and the permissible bounds of uncertainty variation. We present the results of experiments on a quadrocopter with an F450 frame and the results of a comparative analysis of the proposed approach with the one using linear control.
References
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2. Leal I.S., Abeykoon C., Perera, Y.S. Design, Simulation, Analysis and Optimization of PID and Fuzzy Based Control Systems for a Quadcopter. Electronics. 2021. vol. 10. no. 18. pp. 1–33.
3. Abdulkareem A., Oguntosin V., Popoola O.M., Idowu A.A. Modeling and Nonlinear Control of a Quadcopter for Stabilization and Trajectory Tracking. Journal of Engineering. 2022. vol. 2022. pp. 1–19.
4. Shmalko E.Ju. [Machine synthesized control of a nonlinear dynamic plant based on optimal arrangement of equilibrium points]. Informatika i avtomatizacija – Informatics and automation. 2024. vol. 22. no. 1. pp. 87–109. (In Russ).
5. Barsegjan V.R., Simonjan T.A., Matevosjan A.G. [On one problem of optimal control of a quadrocopter with a given intermediate value of a part of phase vector coordinates]. Differencial'nye uravnenija i processy upravlenija – Differential equations and control processes. 2024. no. 2. pp. 59–72. (In Russ).
6. Ferede R., de Croon G., De Wagter C., Izzo D. End-to-end neural network based optimal quadcopter control. Robotics and Autonomous Systems. 2024. vol. 172. pp. 1–11.
7. Borisov O.I., Kakanov M.A., Zhivickij A.Ju., Pyrkin A.A. [Robust output trajectory control of quadrocopter based on geometric approach]. Priborostroenie. – Instrument engineering. 2021. vol. 64. no. 12. pp. 982–992. (In Russ).
8. Nguyen N.P., Pitakwachara P. Integral terminal sliding mode fault tolerant control of quadcopter UAV systems. Sci Rep. 2024. vol. 14. pp. 1–16.
9. Rahmi E., Karaarslan A. Sliding Mode Control-Based Modeling and Simulation of a Quadcopter. Journal of Engineering Research and Reports. 2023. vol. 24. no. 3. pp. 32–41.
10. Jacun S.F., Emel'janova O.V., Santjago Martinez Leon A., Migel Moskera Morocho L. [Adaptive control of a nonlinear plant of the convertoplane type under uncertainties]. Izvestija Jugo-Zapadnogo gosudarstvennogo universiteta – Proceedings of South-West State University. 2020. vol. 24. no. 3. pp. 35–50. (In Russ).
11. Glushhenko A.I., Lastochkin K.A. Exponentially Stable Adaptive Control. Part III. Time-Varying Plants. Avtomatika i telemehanika – Automation and Remote Control. 2023. vol. 84. no. 11. pp. 1232–1247. (In Russ).
12. Glushhenko A.I., Lastochkin K.A. Adaptive Observer of State and Disturbances for Linear Overparameterized Systems. Avtomatika i telemehanika – Automation and Remote Control. 2023. vol. 84. no. 11. pp. 115-146. (In Russ).
13. Xie W., Cabecinhas D., Cunha R., Silvestre C. Adaptive Backstepping Control of a Quadcopter With Uncertain Vehicle Mass, Moment of Inertia, and Disturbances. IEEE Transactions on Industrial Electronics. 2023. vol. 69. no. 1. pp. 549–559. DOI: 10.1109/TIE.2021.3055181.
14. Noordin A., Mohd Basri M.A., Mohamed Z. Real-Time Implementation of an Adaptive PID Controller for the Quadrotor MAV Embedded Flight Control System. Aerospace. 2023. vol. 10. no. 1. DOI: 10.3390/aerospace10010059.
15. Park D., Le T.-L., Quynh N.V., Long N.K., Hong S.K. Online Tuning of PID Controller Using a Multilayer Fuzzy Neural Network Design for Quadcopter Attitude Tracking Control. Frontiers in Neurorobotics. 2021. vol. 14. DOI: 10.3389/fnbot.2020.619350.
16. Ramírez-Neria M., Luviano-Juárez A., González-Sierra J., Ramírez-Juárez R., Aguerrebere J., Hernandez-Martinez E.G. Active Disturbance Rejection Control for the Trajectory Tracking of a Quadrotor. Actuators. 2024. vol. 13. no. 9. DOI: 10.3390/act13090340.
17. Khadraoui S., Fareh R., Baziyad M., Elbeltagy M., Bettayeb M. A Comprehensive Review and Applications of Active Disturbance Rejection Control for Unmanned Aerial Vehicles. IEEE Access. 2024. vol. 12. pp. 185851–185868.
18. Chang X., Jin C., Cheng Y. Dynamics and advanced active disturbance rejection control of tethered UAV. Applied Mathematical Modelling. 2024. vol. 135. pp. 640–665.
19. Buj V.H., Margun A.A., Bobcov A.A. [Synthesis of state variable observer and sinusoidal perturbation for linear nonstationary system with unknown parameters]. Izvestija vysshih uchebnyh zavedenij: Priborostroenie. – Proceedings of Higher Educational Institutions: Instrument engineering. 2024. vol. 67. no. 3. pp. 209–219. (In Russ).
20. Andrievskij B.R., Furtat I.B. Disturbance Observers: Methods and Applications. I. Methods. Avtomatika i telemehanika – Automate and remote control. 2020. no. 9. pp. 3–61. (In Russ).
21. Sun H., Li, J., Wang, R., Yang K. Attitude Control of the Quadrotor UAV with Mismatched Disturbances Based on the Fractional-Order Sliding Mode and Backstepping Control Subject to Actuator Faults. Fractal Fract. 2023. vol. 7. no. 3. DOI: 10.3390/fractalfract7030227.
22. Smith S., Pan Y.-J. Adaptive Observer-Based Super-Twisting Sliding Mode Control for Low Altitude Quadcopter Grasping. IEEE/ASME Transactions on Mechatronics. 2025. vol. 30. no. 1. pp. 587–598.
23. Bingul Z., Gul K. Intelligent-PID with PD Feedforward Trajectory Tracking Control of an Autonomous Underwater Vehicle. Machines. 2023. vol. 11. no. 2. DOI: 10.3390/machines11020300.
24. Rao J., Li B., Zhang Z., Chen D., Giernacki W. Position Control of Quadrotor UAV Based on Cascade Fuzzy Neural Network. Energies. 2022. vol. 15. no. 5. DOI: 10.3390/en15051763.
25. Antipov A.S., Kokunko J.G., Krasnova S.A., Utkin V.A., Utkin A.V. Direct control of the endpoint of the manipulator under non-smooth uncertainty and reference trajectories. Journal of the Franklin Institute. 2023. vol. 360. no. 17. pp. 13430–13458.
26. Golubev A.E., Glazkov T.V. Nonlinear quadrotor control based on Simulink Support Package for Parrot Minidrones. CEUR Workshop Proceedings. 2020. vol. 2783. pp. 113–127.
27. Bici A., Minervini A., Godio S., Guglieri G., Dovis F. Development and Validation of a LQR-Based Quadcopter Control Dynamics Simulation Model. International Journal of Aerospace Engineering. 2021. vol. 34. no. 6. DOI: 10.1061/(ASCE)AS.1943-5525.0001336.
28. Okasha M., Kralev J., Islam M. Design and Experimental Comparison of PID, LQR and MPC Stabilizing Controllers for Parrot Mambo Mini-Drone. Aerospace. 2022. vol. 9. no. 6. DOI: 10.3390/aerospace9060298.
29. Ahn H., Hu M., Chung Y., You K. Sliding-Mode Control for Flight Stability of Quadrotor Drone Using Adaptive Super-Twisting Reaching Law. Drones. 2023. vol. 7. no. 8. DOI: 10.3390/drones7080522.
30. Krasnova S.A., Kokunko J.G., Kochetkov S.A., Utkin V.A. Generation of Achievable Three-Dimensional Trajectories for Autonomous Wheeled Vehicles via Tracking Differentiators. Algorithms. 2023. vol. 16. no. 9. DOI: 10.3390/a16090405.
31. Antipov A., Krasnova S., Utkin V. Methods of Ensuring Invariance with Respect to External Disturbances: Overview and New Advances. Mathematics. 2021. vol. 9. no. 23. DOI: 10.3390/math9233140.
32. Izadi M., Faieghi R. High-gain disturbance observer for robust trajectory tracking of quadrotors. Control Engineering Practice. 2024. vol. 145. DOI: 10.1016/j.conengprac.2024.105854.
33. Volf D.A., Shirokov A.S. [Study of basic and related processes of flight control of quadrocopter system]. Trudy 14-go Vserossijskogo soveshhanija po problemam upravlenija [Proceedings of the 14th All-Russian Meeting on Control Problems]. Moscow: ICS RAS, 2024. pp. 1265–1269. (In Russ.).
34. Wolf D., Alexandrov V., Shatov D., Rezkov I., Trefilov P., Meshcheryakov R. Development of a Firmware for Multirotor UAV Flight Controller Implemented on MCU MDR 32. Proceeding of the International Conference on Interactive Collaborative Robotics (ICR 2023). 2023. vol. 14214. pp. 345–356.
35. Alexandrov V., Rezkov I., Shatov D., Morozov Y. Frequency domain identification of the quadcopter attitude dynamics. Advances in Systems Science and Applications. 2023. vol. 23. no. 3. DOI: 10.25728/assa.2023.23.3.1424.
36. Herbst G. A Simulative Study on Active Disturbance Rejection Control (ADRC) as a Control Tool for Practitioners. Electronics. 2013. vol. 3(2). pp. 246–279.
Published
2025-06-25
How to Cite
Antipov, A., Kokunko, J., Wolf, D., & Shirokov, A. (2025). Synthesis of Combined Quadrocopter Attitude and Altitude Control Based on Block Approach with Sigmoidal Feedbacks. Informatics and Automation, 24(3), 745-790. https://doi.org/10.15622/ia.24.3.2
Section
Robotics, Automation and Control Systems
Copyright (c) Алексей Антипов, Юлия Кокунько, Данияр Вольф, Александр Широков
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