Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/152317
Title: Adaptive control of unmanned quadrotor with partial actuator failure using model reference adaptive control (MRAC) with dynamic inversion
Authors: Agarwal, Anmol
Ng, Ee Meng
Low, Kin Huat
Keywords: Engineering::Mechanical engineering
Issue Date: 2021
Source: Agarwal, A., Ng, E. M. & Low, K. H. (2021). Adaptive control of unmanned quadrotor with partial actuator failure using model reference adaptive control (MRAC) with dynamic inversion. 2021 International Conference on Unmanned Aircraft Systems (ICUAS), 10-19. https://dx.doi.org/10.1109/ICUAS51884.2021.9476830
Abstract: Unmanned Aerial Vehicles (UAVs) often experience disturbances during operation, which will degrade its performance and may cause potential failure, affecting safety risks to civilians and other 3rd parties. In such event, UAVs with the common cascaded PID control might not be sufficient to compensate for this reduction in performance. This paper proposes to analyze algorithm for adaptive control, mainly focused on the model reference adaptive control (MRAC) such that despite any uncertainty the plant parameters remain close to the behavior of a desired reference model along with dynamic inversion as an adaptive controller for such scenarios which helps in decoupling of the flight states for the non-linear system. The results of the proposed method have been compared with the conventional PID based controller by implanting faults in motor outputs. In addition, the performance of the controls is evaluated in terms of trajectory following capability.
URI: https://hdl.handle.net/10356/152317
ISBN: 978-1-6654-1535-4
ISSN: 2575-7296
DOI: 10.1109/ICUAS51884.2021.9476830
Rights: © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: https://doi.org/10.1109/ICUAS51884.2021.9476830.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:ATMRI Conference Papers
MAE Conference Papers

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