In-Ground-Effect Modeling and Nonlinear-Disturbance Observer for Multirotor Unmanned Aerial Vehicle Control

Author:

He Xiang1,Kou Gordon1,Calaf Marc2,Leang Kam K.3

Affiliation:

1. Design, Automation, Robotics, and Control (DARC) Lab, Salt Lake City, UT 84112

2. Wind Energy and Turbulence Laboratory, Salt Lake City, UT 84112

3. Mem. ASME Department of Mechanical Engineering, Design, Automation, Robotics, and Control (DARC) Lab, University of Utah Robotics Center, University of Utah, Salt Lake City, UT 84112 e-mail:

Abstract

This paper focuses on modeling and control of in-ground-effect (IGE) on multirotor unmanned aerial vehicles (UAVs). As the vehicle flies and hovers over, around, or underneath obstacles, such as the ground, ceiling, and other features, the IGE induces a change in thrust that drastically affects flight behavior. This effect on each rotor can be vastly different as the vehicle's attitude varies, and this phenomenon limits the ability for precision flight control, navigation, and landing in tight and confined spaces. An exponential model describing this effect is proposed, analyzed, and validated through experiments. The model accurately predicts the quasi-steady IGE for an experimental quadcopter UAV. To compensate for the IGE, a model-based feed-forward controller and a nonlinear-disturbance observer (NDO) are designed for closed-loop control. Both controllers are validated through physical experiments, where results show approximately 23% reduction in the tracking error using the NDO compared to the case when IGE is not compensated for.

Publisher

ASME International

Subject

Computer Science Applications,Mechanical Engineering,Instrumentation,Information Systems,Control and Systems Engineering

Reference57 articles.

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2. Adams, S. M., and Friedland, C. J., 2011, “A Survey of Unmanned Aerial Vehicle (UAV) Usage for Imagery Collection in Disaster Research and Management,” Ninth International Workshop on Remote Sensing for Disaster Response, Stanford, CA, Sept. 15–16.https://pdfs.semanticscholar.org/fd8e/960ca48e183452335743c273ea41c6930a75.pdf

3. Opportunities and Challenges With Autonomous Micro Aerial Vehicles;Int. J. Rob. Res.,2012

4. Bartholomew, J., Calway, A., and Mayol-Cuevas, W., 2015, “Improving MAV Control by Predicting Aerodynamic Effects of Obstacles,” International Conference on Intelligent Robots and Systems (IROS), Hamburg, Germany, Sept. 28–Oct. 2, pp. 4826–4833.10.1109/IROS.2015.7354055

5. Robinson, D. C., Chung, H., and Ryan, K., 2014, “Computational Investigation of Micro Helicopter Near-Wall Effect,” Australasian Fluid Mechanics Conference, Melbourne, Australia, Dec. 8–11, pp. 8–11.https://people.eng.unimelb.edu.au/imarusic/proceedings/19/278.pdf

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