Neuro-fuzzy controller for attitude-tracking stabilization of a multi-rotor unmanned aerial system

Jorge Cervantes, Filiberto Muñoz, Iván González-Hernández, Sergio Salazar, Isaac Chairez, Rogelio Lozano

Research output: Contribution to conferencePaper

4 Scopus citations

Abstract

© 2017 IEEE. This paper deals with developing an automatic controller that solves the attitude stabilization for a Quadrotor unmanned aerial system (UAS). The controller used a simultaneous strategy of estimation and compensation of uncertainties as well as disturbances. The approach consisted of integrating a neuro-fuzzy system that implemented a set of differential neural networks (DNNs) as consequence section of Takagi-Sugeno (T-S) fuzzy inference. The combination of these two strategies applied on a Quadrotor UAS has the main purpose of forcing a hover flight while the tracking desired angular positions are attained. The control method identified the unknown nonlinearities and bounded external disturbances firstly. This information served to compensate the uncertain section of the Quadrotor dynamics. An additional section in the controller design enforces the stabilization of the tracking error with respect to a given reference trajectory. The control design methodology supported on the Lyapunov stability theory and guaranteed ultimate boundedness of the identification and tracking errors. Academic simulation tests confirmed the superior performance of the proposed algorithm based on the combination of DNNs and T-S techniques.
Original languageAmerican English
Pages1816-1823
Number of pages1633
DOIs
StatePublished - 25 Jul 2017
Event2017 International Conference on Unmanned Aircraft Systems, ICUAS 2017 -
Duration: 25 Jul 2017 → …

Conference

Conference2017 International Conference on Unmanned Aircraft Systems, ICUAS 2017
Period25/07/17 → …

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Cervantes, J., Muñoz, F., González-Hernández, I., Salazar, S., Chairez, I., & Lozano, R. (2017). Neuro-fuzzy controller for attitude-tracking stabilization of a multi-rotor unmanned aerial system. 1816-1823. Paper presented at 2017 International Conference on Unmanned Aircraft Systems, ICUAS 2017, . https://doi.org/10.1109/ICUAS.2017.7991449