Warren, Robin (2023) Integrating Advanced Sizing and Controllability Assessment Methods into an MDO Framework for Optimal Redundancy in UAV Design. Masters thesis, Concordia University.
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Abstract
Electrically-powered multirotor Unmanned Aerial Vehicles ( UAV) are highly susceptible to rotor loss failures, which can result in catastrophic events in urban centers. Redundancy implementation can improve reliability, but heavily affects multirotor UAV performance. Hence, this research work aims at developing a design framework that may optimize multirotor UAVs for both performance and reliability. For this matter, a controllability assessment will be implemented in the design
of multirotor UAVs to ensure fault-tolerant design. An exploration of the design methodologies of multirotor UAVs demonstrates that only one
includes redundancy analysis linked to controllability. The methodologies are classified into three major groups: empirical, analytical modeling and simulations, and analytical catalog-based. These classes are compared in a case study to demonstrate that analytical modeling and simulations are best suited for redundancy implementation due to their affinity with both innovation and reliability. Since traditional controllability is not sufficient for multirotor UAVs, alternatives are evaluated. The Degree of Controllability ( DoC) is chosen since it possesses recovery time requirement potential and the simple inclusion of disturbances. After modification for the application of the DoC to multirotor UAVs, it is implemented within the optimization framework of an analytical modeling and simulation design methodology, optimizing multirotor UAVs for both performance and reliability. The potential recovery time requirements of the DoC prove inconclusive because its value scales with time. Future works, through reference recovery regions, could forge toward aircraft-level controllability requirements. Nevertheless, including the DoC as a constraint yields fault-tolerant designs at a severe cost in computing time.
Divisions: | Concordia University > Gina Cody School of Engineering and Computer Science > Mechanical, Industrial and Aerospace Engineering |
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Item Type: | Thesis (Masters) |
Authors: | Warren, Robin |
Institution: | Concordia University |
Degree Name: | M.A. Sc. |
Program: | Mechanical Engineering |
Date: | 4 March 2023 |
Thesis Supervisor(s): | Liscouët, Jonathan |
Keywords: | Multirotor, UAV, Reliability, Controllability, Battery, Sizing, Methodologies, Design, Empirical, Analytical, Modeling, Rotor Loss |
ID Code: | 992170 |
Deposited By: | Robin Warren |
Deposited On: | 21 Jun 2023 14:40 |
Last Modified: | 21 Jun 2023 14:40 |
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