期刊
AEROSPACE SCIENCE AND TECHNOLOGY
卷 76, 期 -, 页码 455-465出版社
ELSEVIER FRANCE-EDITIONS SCIENTIFIQUES MEDICALES ELSEVIER
DOI: 10.1016/j.ast.2018.02.020
关键词
Unmanned aerial vehicles; Identification; Unscented Kalman filter; Model predictive control; Quad rotor; Interaction control
资金
- SINGA scholarship [SING-2014-2-0256]
Unmanned aerial vehicle (UAV) applications have become increasingly vital, especially when human operators have limited access to the mission such as an inspection of a deep sewerage tunnel system. The problem arises when the UAV is deployed to perform a pre-defined operation, particularly in close proximity to the environment. When the UAV flies within a few centimeters away from its surrounding environment, the ceiling effect problem might occur, which will affect the flight performance. This paper presents the utilization of a centralized predictive interaction control by leveraging an identified nonlinear model of a quadrotor UAV to mitigate the problem. In the first step, real-time data is collected for translational states of the system to identify its aerodynamic parameters. Secondly, a centralized predictive controller is applied to the system in real-time to compensate for the ceiling effect. Finally, the proposed approach is validated numerically and experimentally in free-flight and ceiling interaction phases. The results show that the optimization-based controller with a centralized algorithm is able to converge within 5 ms. (C) 2018 Elsevier Masson SAS. All rights reserved.
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