TY - GEN
T1 - The design of adaptive anti-skid control based on the slip rate constraints
AU - Zhao, Pu
AU - Liang, Na
AU - Yuan, Zhaohui
AU - Lu, Jiuli
AU - Zeng, Zhi
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/11/15
Y1 - 2018/11/15
N2 - In the aircraft anti-skid braking system, the traditional 'PD+PBM' control method can only realize good control on dry runway, but performs poorly on wet runway. In this paper, an adaptive anti-skid control method based on the Lyapunov function constraint control theory of asymmetric obstacles using slip rate constraint is proposed to meet the anti-skid requirements of runway braking under various working conditions. At the same time, BP neural network is used to optimize the model parameters to obtain the most realistic effect. The algorithm uses MATLAB for simulation verification and semi-physical simulation verification on a certain type of inertial test bench. Simulation results show that the adaptive anti-skid control method based on slip ratio constraint can achieve the desired effect, and its performance is greatly improved compared with the traditional method.
AB - In the aircraft anti-skid braking system, the traditional 'PD+PBM' control method can only realize good control on dry runway, but performs poorly on wet runway. In this paper, an adaptive anti-skid control method based on the Lyapunov function constraint control theory of asymmetric obstacles using slip rate constraint is proposed to meet the anti-skid requirements of runway braking under various working conditions. At the same time, BP neural network is used to optimize the model parameters to obtain the most realistic effect. The algorithm uses MATLAB for simulation verification and semi-physical simulation verification on a certain type of inertial test bench. Simulation results show that the adaptive anti-skid control method based on slip ratio constraint can achieve the desired effect, and its performance is greatly improved compared with the traditional method.
KW - Aircraft anti-skid braking system
KW - BP neural network
KW - Lyapunov function constraint control theory of asymmetric obstacles
UR - http://www.scopus.com/inward/record.url?scp=85059836076&partnerID=8YFLogxK
U2 - 10.1109/ICMCCE.2018.00054
DO - 10.1109/ICMCCE.2018.00054
M3 - 会议稿件
AN - SCOPUS:85059836076
T3 - Proceedings - 2018 3rd International Conference on Mechanical, Control and Computer Engineering, ICMCCE 2018
SP - 230
EP - 235
BT - Proceedings - 2018 3rd International Conference on Mechanical, Control and Computer Engineering, ICMCCE 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 3rd International Conference on Mechanical, Control and Computer Engineering, ICMCCE 2018
Y2 - 14 September 2018 through 16 September 2018
ER -