Benchmarking Tracking Autopilots for Quadrotor Aerial Robotic System Using Heuristic Nonlinear Controllers
This paper investigates and benchmarks quadrotor navigation and hold autopilots’ global control performance using heuristic optimization algorithms. The compared methods offer advantages in terms of computational effectiveness and efficiency to tune the optimum controller gains for highly nonlinear...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-11-01
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| Series: | Drones |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2504-446X/6/12/379 |
| _version_ | 1797460467408437248 |
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| author | Muhammad Bakr Abdelghany Ahmed M. Moustafa Mohammed Moness |
| author_facet | Muhammad Bakr Abdelghany Ahmed M. Moustafa Mohammed Moness |
| author_sort | Muhammad Bakr Abdelghany |
| collection | DOAJ |
| description | This paper investigates and benchmarks quadrotor navigation and hold autopilots’ global control performance using heuristic optimization algorithms. The compared methods offer advantages in terms of computational effectiveness and efficiency to tune the optimum controller gains for highly nonlinear systems. A nonlinear dynamical model of the quadrotor using the Newton–Euler equations is modeled and validated. Using a modified particle swarm optimization (MPSO) and genetic algorithm (GA) from the heuristic paradigm, an offline optimization problem is formulated and solved for three different controllers: a proportional–derivative (PD) controller, a nonlinear sliding-mode controller (SMC), and a nonlinear backstepping controller (BSC). It is evident through the simulation case studies that the utilization of heuristic optimization techniques for nonlinear controllers considerably enhances the quadrotor system response. The performance of the conventional PD controller, SMC, and BSC is compared with heuristic approaches in terms of stability and influence of internal and external disturbance, and system response using the MATLAB/SIMULINK environment. The simulation results confirm the reliability of the proposed tuned GA and MPSO controllers. The PD controller gives the best performance when the quadrotor system operates at the equilibrium point, while SMC and BSC approaches give the best performance when the system does an aggressive maneuver outside the hovering condition. The overall final results show that the GA-tuned controllers can serve as a benchmark for comparing the global performance of aerial robotic control loops. |
| first_indexed | 2024-03-09T17:05:30Z |
| format | Article |
| id | doaj.art-7de289f22a504e98a267d0ea5a5c61fd |
| institution | Directory Open Access Journal |
| issn | 2504-446X |
| language | English |
| last_indexed | 2024-03-09T17:05:30Z |
| publishDate | 2022-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Drones |
| spelling | doaj.art-7de289f22a504e98a267d0ea5a5c61fd2023-11-24T14:24:40ZengMDPI AGDrones2504-446X2022-11-0161237910.3390/drones6120379Benchmarking Tracking Autopilots for Quadrotor Aerial Robotic System Using Heuristic Nonlinear ControllersMuhammad Bakr Abdelghany0Ahmed M. Moustafa1Mohammed Moness2Group for Research on Automatic Control Engineering, Department of Engineering, University of Sannio, Piazza Roma 21, 82100 Benevento, ItalyComputer and Systems Engineering Department, Faculty of Engineering, Minia University, Minia 61111, EgyptComputer and Systems Engineering Department, Faculty of Engineering, Minia University, Minia 61111, EgyptThis paper investigates and benchmarks quadrotor navigation and hold autopilots’ global control performance using heuristic optimization algorithms. The compared methods offer advantages in terms of computational effectiveness and efficiency to tune the optimum controller gains for highly nonlinear systems. A nonlinear dynamical model of the quadrotor using the Newton–Euler equations is modeled and validated. Using a modified particle swarm optimization (MPSO) and genetic algorithm (GA) from the heuristic paradigm, an offline optimization problem is formulated and solved for three different controllers: a proportional–derivative (PD) controller, a nonlinear sliding-mode controller (SMC), and a nonlinear backstepping controller (BSC). It is evident through the simulation case studies that the utilization of heuristic optimization techniques for nonlinear controllers considerably enhances the quadrotor system response. The performance of the conventional PD controller, SMC, and BSC is compared with heuristic approaches in terms of stability and influence of internal and external disturbance, and system response using the MATLAB/SIMULINK environment. The simulation results confirm the reliability of the proposed tuned GA and MPSO controllers. The PD controller gives the best performance when the quadrotor system operates at the equilibrium point, while SMC and BSC approaches give the best performance when the system does an aggressive maneuver outside the hovering condition. The overall final results show that the GA-tuned controllers can serve as a benchmark for comparing the global performance of aerial robotic control loops.https://www.mdpi.com/2504-446X/6/12/379heuristic algorithmsmodelingnonlinear sliding mode controlnonlinear backstepping controlPDquadrotor |
| spellingShingle | Muhammad Bakr Abdelghany Ahmed M. Moustafa Mohammed Moness Benchmarking Tracking Autopilots for Quadrotor Aerial Robotic System Using Heuristic Nonlinear Controllers Drones heuristic algorithms modeling nonlinear sliding mode control nonlinear backstepping control PD quadrotor |
| title | Benchmarking Tracking Autopilots for Quadrotor Aerial Robotic System Using Heuristic Nonlinear Controllers |
| title_full | Benchmarking Tracking Autopilots for Quadrotor Aerial Robotic System Using Heuristic Nonlinear Controllers |
| title_fullStr | Benchmarking Tracking Autopilots for Quadrotor Aerial Robotic System Using Heuristic Nonlinear Controllers |
| title_full_unstemmed | Benchmarking Tracking Autopilots for Quadrotor Aerial Robotic System Using Heuristic Nonlinear Controllers |
| title_short | Benchmarking Tracking Autopilots for Quadrotor Aerial Robotic System Using Heuristic Nonlinear Controllers |
| title_sort | benchmarking tracking autopilots for quadrotor aerial robotic system using heuristic nonlinear controllers |
| topic | heuristic algorithms modeling nonlinear sliding mode control nonlinear backstepping control PD quadrotor |
| url | https://www.mdpi.com/2504-446X/6/12/379 |
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