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Optimal Trajectory Tracking: A Comparative Study of Autonomous Quadcopter Controllers.
- Source :
-
Jordan Journal of Mechanical & Industrial Engineering . Jun2024, Vol. 18 Issue 2, p411-419. 9p. - Publication Year :
- 2024
-
Abstract
- The quadcopter controller plays a significant role in autonomous vehicle trajectory tracking and has been extensively examined in the literature because it is a highly nonlinear and under-actuated system. This article contributes by methodically comparing PID, BSC, IBSC, SMC, and ISMC control algorithms under standardized conditions. The study involves implementing these algorithms and optimizing their parameters using a hybrid Flower Pollination Algorithm - Genetic Algorithm (FPA-GA). Robust testing scenarios, including mass uncertainty and time-varying disturbances, are employed to assess algorithmic performance. The research centers on trajectory tracking-control approaches for highly maneuverable Unmanned Aerial Vehicles (UAVs) equipped with four heave thrusters, emphasizing controller stability through Lyapunov functions. Theoretical exploration precedes comprehensive numerical simulations, enabling a detailed comparison of the efficacy and resilience of the proposed approaches. Results from exhaustive testing reveal the consistent superiority of the BSC controller, demonstrating notably low Integral of Time-weighted Squared Error (ITSE) values of 0.1253 and 0.5262 from two simulation tests. These findings underscore the practical advantages of the BSC controller in highly dynamic UAV trajectory tracking scenarios. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 19956665
- Volume :
- 18
- Issue :
- 2
- Database :
- Academic Search Index
- Journal :
- Jordan Journal of Mechanical & Industrial Engineering
- Publication Type :
- Academic Journal
- Accession number :
- 178847836
- Full Text :
- https://doi.org/10.59038/jjmie/180213