Abstract
Quadrotors have been more frequently used in different areas, from aerial photography to drug delivery in medical emergencies. These vehicles have high maneuverability, which makes them suitable for carrying out missions that humans would not be able to do due to physical constraints. They can be used in inhospitable environments where the physical integrity and health of humans would be compromised. However, they are highly nonlinear and multivariable systems whose dynamics are strongly coupled. These characteristics turn attitude control design into a complex task. Furthermore, the controller has to be able to deal with uncertainties and exogenous disturbances in practice, intensifying the difficulty of the control problem. Therefore, a quadrotor attitude control must have high robustness and fast response without compromising its global stability. Aiming to gather solutions to this control problem, this article provides a detailed and in-depth discussion on quadrotor attitude control strategies for flight control designers, including angular representation, controller stability, fault tolerance, actuator saturation, and strategies for exogenous disturbance rejection.
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Funding
The authors thank the National Council for Scientific and Technological Development (CNPq). This study was financed by the Human Resource Program of the Brazilian National Agency for Petroleum, Natural Gas, and Biofuels – PRH-ANP, supported by resources from oil companies considering contract clause no 50/2015 of R, D &I of the ANP.
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PJDOE: Conceptualization; Methodology; Formal analysis and investigation; Writing - original draft preparation. VMA: Formal analysis and investigation; Writing - review and editing. CBS: Formal analysis and investigation; Writing - review and editing. DSC: Formal analysis and investigation; Writing - review and editing. PMP: Data curation. SSCB: Funding acquisition. PLJDJ: Resources; Supervision.
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de Oliveira Evald, P.J.D., Aoki, V.M., da Silva, C.B. et al. A review on quadrotor attitude control strategies. Int J Intell Robot Appl 8, 230–250 (2024). https://doi.org/10.1007/s41315-023-00308-9
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DOI: https://doi.org/10.1007/s41315-023-00308-9