TY - GEN
T1 - Neuro-fuzzy controller for attitude-tracking stabilization of a multi-rotor unmanned aerial system
AU - Cervantes, Jorge
AU - Muñoz, Filiberto
AU - González-Hernández, Iván
AU - Salazar, Sergio
AU - Chairez, Isaac
AU - Lozano, Rogelio
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/7/25
Y1 - 2017/7/25
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85034075640&partnerID=8YFLogxK
U2 - 10.1109/ICUAS.2017.7991449
DO - 10.1109/ICUAS.2017.7991449
M3 - Contribución a la conferencia
AN - SCOPUS:85034075640
T3 - 2017 International Conference on Unmanned Aircraft Systems, ICUAS 2017
SP - 1816
EP - 1823
BT - 2017 International Conference on Unmanned Aircraft Systems, ICUAS 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2017 International Conference on Unmanned Aircraft Systems, ICUAS 2017
Y2 - 13 June 2017 through 16 June 2017
ER -