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Thrust Mixing, Saturation, and Body-Rate Control for Accurate Aggressive Quadrotor Flight

Faessler, Matthias; Falanga, Davide; Scaramuzza, Davide (2017). Thrust Mixing, Saturation, and Body-Rate Control for Accurate Aggressive Quadrotor Flight. IEEE Robotics and Automation Letters, 2(2):476-482.

Abstract

Quadrotors are well suited for executing fast maneuvers with high accelerations but they are still unable to follow a fast trajectory with centimeter accuracy without iteratively learning it beforehand. In this paper, we present a novel body-rate controller and an iterative thrust-mixing scheme, which improve the trajectory-tracking performance without requiring learning and reduce the yaw control error of a quadrotor, respectively. Furthermore, to the best of our knowledge, we present the first algorithm to cope with motor saturations smartly by prioritizing control inputs which are relevant for stabilization and trajectory tracking. The presented body-rate controller uses LQR-control methods to consider both the body rate and the single motor dynamics, which reduces the overall trajectory-tracking error while still rejecting external disturbances well. Our iterative thrust-mixing scheme computes the four rotor thrusts given the inputs from a position-control pipeline. Through the iterative computation, we are able to consider a varying ratio of thrust and drag torque of a single propeller over its input range, which allows applying the desired yaw torque more precisely and hence reduces the yaw-control error. Our prioritizing motor-saturation scheme improves stability and robustness of a quadrotor's flight and may prevent unstable behavior in case of motor saturations. We demonstrate the improved trajectory tracking, yaw-control, and robustness in case of motor saturations in real-world experiments with a quadrotor.

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Informatics
Dewey Decimal Classification:000 Computer science, knowledge & systems
Scopus Subject Areas:Physical Sciences > Control and Systems Engineering
Physical Sciences > Biomedical Engineering
Physical Sciences > Human-Computer Interaction
Physical Sciences > Mechanical Engineering
Physical Sciences > Computer Vision and Pattern Recognition
Physical Sciences > Computer Science Applications
Physical Sciences > Control and Optimization
Physical Sciences > Artificial Intelligence
Scope:Discipline-based scholarship (basic research)
Language:English
Date:April 2017
Deposited On:26 Feb 2024 10:56
Last Modified:27 Feb 2025 02:42
Publisher:Institute of Electrical and Electronics Engineers
ISSN:2377-3766
OA Status:Green
Publisher DOI:https://doi.org/10.1109/LRA.2016.2640362
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  • Content: Accepted Version
  • Language: English
  • Licence: Creative Commons: Attribution 4.0 International (CC BY 4.0)

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