Control adaptable basado en el regresor para seguimiento de trayectorias aplicado a un quadrotor

Ivan Alonso Lopez-Sanchez; Eduardo Javier Moreno-Valenzuela; Ricardo Ramón Pérez-Alcocer

doi:10.29057/icbi.v10iEspecial4.9191

Ivan Alonso Lopez-Sanchez Instituto Politécnico Nacional https://orcid.org/0000-0002-7263-7356
Eduardo Javier Moreno-Valenzuela Instituto Politécnico Nacional https://orcid.org/0000-0003-0670-5979
Ricardo Ramón Pérez-Alcocer Universidad de Sonora https://orcid.org/0000-0002-1543-3701

DOI: https://doi.org/10.29057/icbi.v10iEspecial4.9191

Palabras clave: Control adaptable, estabilidad de Lyapunov, control no lineal, incertidumbre paramétrica, quadrotor

Resumen

En este documento se presenta un controlador adaptable basado en el regresor que funge como controlador de lazo externo para un quadrotor que ya cuenta con un controlador interno al cual no se tiene acceso. El controlador propuesto está concebido para tareas de seguimiento de trayectorias y operar sin conocimiento previo de los parámetros del quadrotor, así como del controlador interno. La estabilidad del origen del espacio de estados del sistema en lazo cerrado es analizada mediante la teoría de Lyapunov con lo que se obtiene la ley de adaptación de parámetros y reglas de sintonía, garantizando así la convergencia a cero del error de seguimiento de trayectoria y su derivada. Además, los resultados de las simulaciones numéricas validan la funcionalidad del controlador propuesto y se demuestra la robustez de este ante incertidumbre paramétrica.

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Chen, A. Y., Huang, Y.-N., Han, J.-Y., & Kang, S.-C. J. (2014). A review of rotorcraft unmanned aerial vehicle (UAV) developments and applications in civil engineering. Smart Structures and Systems, 13(6):1065--1094. DOI: http://dx.doi.org/10.12989/sss.2014.13.6.1065.

Dupont, Q. F., Chua, D. K., Tashrif, A., & Abbott, E. L. (2017). Potential applications of UAV along the construction's value chain. Procedia Engineering, 182:165--173. DOI: https://doi.org/10.1016/j.proeng.2017.03.155.

Engel, J., Sturm, J., & Cremers, D. (2012). Camera-based navigation of a low-cost quadrocopter. In Proc. IEEE/RSJ International Conference on Intelligent Robots and Systems, pages 2815--2821. DOI: 10.1109/IROS.2012.6385458.

Falcón, P., Barreiro, A., & Cacho, M. D. (2013). Modeling of Parrot Ardrone and passivity-based reset control. In Proc. 9th Asian Control Conference, pages 1--6. DOI: 10.1109/ASCC.2013.6606362.

Idrissi, M., Salami, M., & Annaz, F. (2022). A review of quadrotor unmanned aerial vehicles: Applications, architectural design and control algorithms. Journal of Intelligent & Robotic Systems, 104(2):1--33. DOI: https://doi.org/10.1007/s10846--021--01527--7.

Khalil, H. K. (2002). Nonlinear systems. Prentice-Hall, Upper Saddle River, NJ, USA, 3 edition.

Kim, J., Gadsden, S. A., & Wilkerson, S. A. (2019). A comprehensive survey of control strategies for autonomous quadrotors. Canadian Journal of Electrical and Computer Engineering, 43(1):3--16. DOI: 10.1109/CJECE.2019.2920938.

Kourani, A. & Daher, N. (2021). Marine locomotion: A tethered UAV-buoy system with surge velocity control. Robotics and Autonomous Systems, 145 (103858):1--17. DOI: https://doi.org/10.1016/j.robot.2021.103858.

Lopez-Sanchez, I., Rossomando, F., Pérez-Alcocer, R., Soria, C., Carelli, R., & Moreno-Valenzuela, J. (2021). Adaptive trajectory tracking control for quadrotors with disturbances by using generalized regression neural networks. Neurocomputing, 460:243--255. DOI: https://doi.org/10.1016/j.neucom.2021.06.079.

Mo, H. & Farid, G. (2019). Nonlinear and adaptive intelligent control techniques for quadrotor UAV--a survey. Asian Journal of Control, 21(2):989--1008. DOI: https://doi.org/10.1002/asjc.1758.

Moreno-Valenzuela, J., Pérez-Alcocer, R., Guerrero-Medina, M., & Dzul, A. (2018). Nonlinear PID-type controller for quadrotor trajectory tracking. IEEE/ASME Transactions on Mechatronics, 23(5):2436--2447. DOI: 10.1109/TMECH.2018.2855161.

Nguyen, H., Kamel, M., Alexis, K., & Siegwart, R. (2021). Model predictive control for micro aerial vehicles: A survey. In Proc. European Control Conference, pages 1556--1563. DOI: 10.23919/ECC54610.2021.9654841.

Nguyen, H. T., Quyen, T. V., Nguyen, C. V., Le, A. M., Tran, H. T., & Nguyen, M. T. (2020). Control algorithms for UAVs: A comprehensive survey. EAI Endorsed Transactions on Industrial Networks and Intelligent Systems, 7(23):1--11. DOI: 10.4108/eai.18--5--2020.164586.

Pérez-Alcocer, R. & Moreno-Valenzuela, J. (2019). Adaptive control for quadrotor trajectory tracking with accurate parametrization. IEEE Access, 7:53236--53247. DOI: 10.1109/ACCESS.2019.2912608.

Pérez-Alcocer, R., Moreno-Valenzuela, J., & Miranda-Colorado, R. (2016). A robust approach for trajectory tracking control of a quadrotor with experimental validation. ISA Transactions, 65:262--274. DOI: https://doi.org/10.1016/j.isatra.2016.08.001.

Rosales, C., Rossomando, F., Soria, C., & Carelli, R. (2018). Neural control of a quadrotor: A state-observer based approach. In Proc. Int. Conf. on Unmanned Aircraft Systems}, pages 647--653. DOI: 10.1109/ICUAS.2018.8453303.

Santana, L. V., Brandao, A. S., & Sarcinelli-Filho, M. (2016). Navigation and cooperative control using the AR.Drone quadrotor. Journal of Intelligent & Robotic Systems, 84(1-4):327--350. DOI: https://doi.org/10.1007/s10846--016--0355--y.

Santana, L. V., Brandao, A. S., Sarcinelli-Filho, M., & Carelli, R. (2014). A trajectory tracking and 3D positioning controller for the AR.Drone quadrotor. In Proc. Int. Conf. on Unmanned Aircraft Systems, pages 756--767. DOI: 10.1109/ICUAS.2014.6842321.

Santos, M. C., Santana, L. V., Brandao, A. S., Sarcinelli-Filho, M., & Carelli, R. (2017). Indoor low-cost localization system for controlling aerial robots. Control Engineering Practice, 61:93--111. DOI: https://doi.org/10.1016/j.conengprac.2017.01.011.

Santos, M. C., Santana, L. V., Martins, M. M., Brandao, A. S., & Sarcinelli-Filho, M. (2015). Estimating and controlling UAV position using RGB-D/IMU data fusion with decentralized information/Kalman filter. In Proc. IEEE International Conference on Industrial Technology, pages 232--239. DOI: 10.1109/ICIT.2015.7125104.

Santos, M. C., Sarcinelli-Filho, M., & Carelli, R. (2016). Trajectory tracking for UAV with saturation of velocities. In Proc. International Conference on Unmanned Aircraft Systems, pages 643--648. DOI: 10.1109/ICUAS.2016.7502598.

Santos, M. C. P., Rosales, C. D., Sarapura, J. A., Sarcinelli-Filho, M., & Carelli, R. (2019). An adaptive dynamic controller for quadrotor to perform trajectory tracking tasks. Journal of Intelligent & Robotic Systems}, 93(1):5--16. DOI: https://doi.org/10.1007/s10846--018--0799--3.

Santos, M. C. P., Rosales, C. D., Sarcinelli-Filho, M., & Carelli, R. (2017). A novel null-space-based UAV trajectory tracking controller with collision avoidance. IEEE/ASME Transactions on Mechatronics, 22(6):2543--2553. DOI: 10.1109/TMECH.2017.2752302.

Sarapura, J. A., Roberti, F., Toibero, J. M., Sebastián, J. M., & Carelli, R. (2020). Visual servo controllers for an UAV tracking vegetal paths. In Machine Vision and Navigation, pages 597--625. Springer, Cham, Switzerland. DOI: https://doi.org/10.1007/978-3-030-22587-2_18.

Tomás, K., Vonásek, V., Fiser, D., and Faigl, J. (2011). AR-Drone as a robotic platform for research and education. In Proc. International Conference on Research and Education in Robotics--EUROBOT 2011, pages 172--186. DOI: https://doi.org/10.1007/978--3--642--21975--7_16.

Wang, N. and Ahn, C. K. (2021). Coordinated trajectory-tracking control of a marine aerial-surface heterogeneous system. IEEE/ASME Transactions on Mechatronics, 26(6):3198--3210. DOI: 10.1109/TMECH.2021.3055450.

Zhang, F. (2006). The Schur complement and its applications, volume 4 of Numerical Methods and Algorithms. Springer, Boston, MA, USA.