TY - GEN
T1 - RBF neural network based dynamic surface control for anti-skid braking system using barrier Lyapunov theorem
AU - Sun, Hui
AU - Yan, Jianguo
AU - Qu, Yaohong
AU - Liu, Yuan
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/8/3
Y1 - 2016/8/3
N2 - A method of dynamic surface control, which is based on RBF neural network, is proposed for aircraft anti-skid braking system (ABS). The proposed scheme solves a difficult problem of controller design in the present of output constraints and unknown external disturbance. In this approach, using the RBF neural network approximates to the uncertain nonlinearities of ABS. Subsequently, we demonstrate that the proposed controller can guarantee the boundedness of the output constraints by developing the asymmetric barrier Lyapunov function (ABLF), which makes the wheel slip-ratio constraints more flexible for various runway surfaces and runway transitions. The back-stepping strategy based on dynamic surface control (DSC) is introduced to eliminate repeated differentiation resulting from ABLF synthesis. The proposed scheme can guarantee the stability of the overall system with unknown external disturbance. The results of simulations have validated the effectiveness of the proposed control scheme.
AB - A method of dynamic surface control, which is based on RBF neural network, is proposed for aircraft anti-skid braking system (ABS). The proposed scheme solves a difficult problem of controller design in the present of output constraints and unknown external disturbance. In this approach, using the RBF neural network approximates to the uncertain nonlinearities of ABS. Subsequently, we demonstrate that the proposed controller can guarantee the boundedness of the output constraints by developing the asymmetric barrier Lyapunov function (ABLF), which makes the wheel slip-ratio constraints more flexible for various runway surfaces and runway transitions. The back-stepping strategy based on dynamic surface control (DSC) is introduced to eliminate repeated differentiation resulting from ABLF synthesis. The proposed scheme can guarantee the stability of the overall system with unknown external disturbance. The results of simulations have validated the effectiveness of the proposed control scheme.
KW - Anti-skid Braking System (ABS)
KW - Asymmetric Barrier Lyapunov Function (ABLF)
KW - Dynamic Surface Control (DSC)
KW - Output Constraints
KW - Unknown External Disturbance
UR - http://www.scopus.com/inward/record.url?scp=84983770987&partnerID=8YFLogxK
U2 - 10.1109/CCDC.2016.7531219
DO - 10.1109/CCDC.2016.7531219
M3 - 会议稿件
AN - SCOPUS:84983770987
T3 - Proceedings of the 28th Chinese Control and Decision Conference, CCDC 2016
SP - 1488
EP - 1495
BT - Proceedings of the 28th Chinese Control and Decision Conference, CCDC 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 28th Chinese Control and Decision Conference, CCDC 2016
Y2 - 28 May 2016 through 30 May 2016
ER -