Event-Sampled Control of Quadrotor Unmanned Aerial Vehicle using Neural Networks
Abstract
In this paper, an event-sampled output-feedback neural network (NN) controller for a quadrotor unmanned aerial vehicle (UAV) is considered. First an observer design is presented, allowing the need for a full knowledge of the state-vector to be avoided. Next, a kinematic controller is designed in order to find a desired translational velocity; the information provided by the kinematic controller will be used in the design of a virtual controller wherein a desired rotational velocity will be determined such that the UAV's orientation converges to its desired value. Finally, the information from the observer, the kinematic controller, and the virtual controller are used in the design of a dynamic controller where NNs will be implemented to approximate uncertainties in the UAV's dynamics; the signals generated by the dynamic controller will ensure that the desired lift velocity and the desired rotational velocities are tracked. In all these designs, the effects of sampling errors are highlighted. Next, by designing an appropriate event-execution law, the sampling errors are shown to be bounded during the inter-event period. Finally, the effectiveness of the proposed event-sampled controller will be demonstrated with simulation results.
Recommended Citation
N. Szanto et al., "Event-Sampled Control of Quadrotor Unmanned Aerial Vehicle using Neural Networks," Proceedings of the 2017 American Control Conference (2017, Seattle, WA), pp. 2956 - 2961, Institute of Electrical and Electronics Engineers (IEEE), May 2017.
The definitive version is available at https://doi.org/10.23919/ACC.2017.7963400
Meeting Name
2017 American Control Conference, ACC (2017: May 24-26, Seattle, WA)
Department(s)
Electrical and Computer Engineering
Research Center/Lab(s)
Intelligent Systems Center
Keywords and Phrases
Aircraft control; Kinematics; Unmanned aerial vehicles (UAV); Velocity; Dynamic controller; Kinematic controller; Observer design; Quadrotor unmanned aerial vehicles; Rotational velocity; Sampling errors; Translational velocity; Virtual controller; Controllers
International Standard Book Number (ISBN)
978-1-5090-5992-8
International Standard Serial Number (ISSN)
0743-1619; 2378-5861
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2017 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
Publication Date
01 May 2017
Comments
This research is supported, in part, by NSF ECCS #1406533 and Intelligent Systems Center.