پیوندهای مفید
آمار
| تعداد نشریات | 9 |
| تعداد شمارهها | 452 |
| تعداد مقالات | 5,748 |
| تعداد مشاهده مقاله | 8,234,517 |
| تعداد دریافت فایل اصل مقاله | 6,752,202 |
Formation Tracking of Nonlinear Quadcopters Using Robust Model Predictive Control in Unknown Environments | ||
| AUT Journal of Electrical Engineering | ||
| مقاله 12، دوره 57، شماره 3، 2025، صفحه 611-628 اصل مقاله (3.2 M) | ||
| نوع مقاله: Research Article | ||
| شناسه دیجیتال (DOI): 10.22060/eej.2025.23822.5635 | ||
| نویسندگان | ||
| Navid Mohammadi1؛ Saeed Khankalantary* 2؛ Morteza Tayefi1 | ||
| 1Institute of Intelligent Control Systems, K. N. Toosi University of Technology, Tehran, Iran | ||
| 2Faculty of Electrical Engineering, K. N. Toosi University of Technology, Tehran, Iran | ||
| چکیده | ||
| This study presents a robust framework for formation tracking and cooperative control of multiple nonlinear quadcopters, incorporating actuator dynamics, wind drag, and uncertainties. Instead of using torques and forces as control inputs, the theoretical models are developed based on motor speed controls. Designing a controller directly based on actuator signals minimizes uncertainty, improves real-world applicability, and eliminates the need for an additional control allocation algorithm. Two optimal controllers, Linear Quadratic Regulator and Model Predictive Control, are developed and evaluated under dynamic conditions, including uncertainty, disturbances, and obstacle-laden environments. The error-based Predictive Control design minimizes sensitivity to initial conditions and enhances robustness, outperforming Linear Quadratic Regulator in trajectory tracking, energy efficiency, and stability. This framework is extended to a graph-theoretic multi-agent system with four interconnected quadcopters, employing formation control to navigate complex helical paths while maintaining square formations among uncertainties and obstacles. Integrating advanced control methods and graph theory demonstrates coordination and robustness, validating the system's potential for surveillance, rescue missions, and autonomous transfer applications. This research lays the groundwork for extending these methods to larger, heterogeneous agent teams, which can ensure adaptability and precision in real-world scenarios. | ||
| کلیدواژهها | ||
| Formation Tracking؛ Quadcopter؛ Nonlinear Dynamics؛ Multi-Agent Control؛ Model Predictive Control | ||
| مراجع | ||
|
[1] A. Katiar, R. Rashdi, Z. Ali, U. Baig, Control and stability analysis of quadcopter, in: 2018 International Conference on Computing, Mathematics and Engineering Technologies (iCoMET), IEEE, 2018, pp. 1-6.
[2] O. Harkare, R. Maan, Design and Control of a Quadcopter, Int. J. Eng. Tech. Res, 10(5) (2021).
[3] V.K. Tripathi, L. Behera, N. Verma, Design of sliding mode and backstepping controllers for a quadcopter, in: 2015 39th national systems conference (NSC), IEEE, 2015, pp. 1-6.
[4] X. Luo, N. Han, X. Guan, Leader-following consensus protocols for formation control of multi-agent network, Journal of Systems Engineering and Electronics, 22(6) (2011) 991-997.
[5] Z. Lin, L. Wang, Z. Han, M. Fu, Distributed formation control of multi-agent systems using complex Laplacian, IEEE Transactions on Automatic Control, 59(7) (2014) 1765-1777.
[6] J. Bai, G. Wen, A. Rahmani, Y. Yu, Formation tracking of fractional-order multi-agent systems based on error predictor, in: The 27th Chinese Control and Decision Conference (2015 CCDC), IEEE, 2015, pp. 279-284.
[7] Y.Q. Chen, Z. Wang, Formation control: a review and a new consideration, in: 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, IEEE, 2005, pp. 3181-3186.
[8] H.G. Tanner, On the controllability of nearest neighbor interconnections, in: 2004 43rd IEEE conference on decision and control (CDC)(IEEE Cat. No. 04CH37601), IEEE, 2004, pp. 2467-2472.
[9] P. Ogren, M. Egerstedt, X. Hu, A control Lyapunov function approach to multi-agent coordination, in: Proceedings of the 40th IEEE Conference on Decision and Control (Cat. No. 01CH37228), IEEE, 2001, pp. 1150-1155.
[10] M.H. Yamchi, R.M. Esfanjani, Formation control of networked mobile robots with guaranteed obstacle and collision avoidance, Robotica, 35(6) (2017) 1365-1377.
[11] L. Sabattini, C. Secchi, C. Fantuzzi, Potential-based control strategy for arbitrary shape formations of mobile robots, in: 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, IEEE, 2009, pp. 3762-3767.
[12] K.H. Kowdiki, R.K. Barai, S. Bhattacharya, Leader-follower formation control using artificial potential functions: A kinematic approach, in: IEEE-International Conference On Advances In Engineering, Science And Management (ICAESM-2012), IEEE, 2012, pp. 500-505.
[13] N. Nfaileh, K. Alipour, B. Tarvirdizadeh, A. Hadi, Formation control of multiple wheeled mobile robots based on model predictive control, Robotica, 40(9) (2022) 3178-3213.
[14] S. Vargas, H.M. Becerra, J.-B. Hayet, MPC-based distributed formation control of multiple quadcopters with obstacle avoidance and connectivity maintenance, Control Engineering Practice, 121 (2022) 105054.
[15] L. Hu, K. Tian, C. Bai, Quadcopter Unmanned Aerial Vehicle Formation Trajectory Tracking based on Extended State Observer with Model Predictive Control, in: 2024 7th International Conference on Robotics, Control and Automation Engineering (RCAE), IEEE, 2024, pp. 240-246.
[16] M. Tayefi, Z. Geng, Logarithmic control, trajectory tracking, and formation for nonholonomic vehicles on Lie group SE (2), International Journal of Control, 92(2) (2019) 204-224.
[17] S.M. Zakipour Bahambari, S. Khankalantary, Formation Control of Quadcopters with Unknown Target Tracking and Obstacle Avoidance Using PID and MPC Controller, International Journal of Industrial Electronics Control and Optimization, 8(2) (2025) 165-176.
[18] J. Diebel, Representing attitude: Euler angles, unit quaternions, and rotation vectors, Matrix, 58(15-16) (2006) 1-35.
[19] S. Lu, Modeling, control, and design of a quadrotor platform for indoor environments, Arizona State University, 2018.
[20] H. Bouadi, M. Tadjine, Nonlinear observer design and sliding mode control of four-rotor helicopter, International Journal of Mechanical, Aerospace, Industrial, Mechatronic and Manufacturing Engineering, 1(7) (2007) 354-359.
[21] Q. Quan, Introduction to multicopter design and control, Springer, 2017.
[22] D.E. Kirk, Optimal control theory: an introduction, Courier Corporation, 2004.
[23] L. Wang, Model Predictive Control System Design and Implementation Using MATLAB, in Springer Verlag, 2009.
[24] K.-K. Oh, M.-C. Park, H.-S. Ahn, A survey of multi-agent formation control, Automatica, 53 (2015) 424-440.
[25] W. Ren, Y. Cao, Distributed coordination of multi-agent networks: emergent problems, models, and issues, Springer Science & Business Media, 2010.
[26] G. Hao, Q. Lv, Z. Huang, H. Zhao, W. Chen, UAV path planning based on improved artificial potential field method, Aerospace, 10(6) (2023) 562. | ||
|
آمار تعداد مشاهده مقاله: 354 تعداد دریافت فایل اصل مقاله: 226 |
||