Research on Feedback Compensation Control for Aircraft Electric Antiskid Brake System Based on IL

Authors

Gao Jie, 1. School of Electronic Information and Automation, Civil Aviation University of China, Tianjin 300300, China;;
Gao Bing, 2. Engineering Techniques Training Center, Civil Aviation University of China, Tianjin 300300, China;
Jianying Liu, 1. School of Electronic Information and Automation, Civil Aviation University of China, Tianjin 300300, China;;

Abstract

Abstract: Safety, efficiency and comfort of aircraft are all determined by antiskid braking system. Because of the problem of inadequate control in the anti-skid braking system, the nonlinear model of the aircraft electric braking system was built by the analysis of aircraft landing process, and the iterative learning algorithm was introduced for reciprocating characteristics of anti-skid control. The groups in different speeds and road conditions were trained using the PD type learning rate. The knowledge base on the relationship among the optimal slip ratio and velocity and road conditions was built. The feed-forward control knowledge system for identifying the different road conditions was designed. The anti-disturbance of the system was realized by the feedback compensation control strategy. Simulation results prove that the system can maintain the best slip rate, shorten the braking distance, and finally achieve a smooth brake.

Recommended Citation

Jie, Gao; Bing, Gao; and Liu, Jianying (2020) "Research on Feedback Compensation Control for Aircraft Electric Antiskid Brake System Based on IL," Journal of System Simulation: Vol. 29: Iss. 7, Article 30.
DOI: 10.16182/j.issn1004731x.joss.201707030
Available at: https://dc-china-simulation.researchcommons.org/journal/vol29/iss7/30

First Page

1625

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.201707030

Last Page

1630

CLC

V227+.5

Recommended Citation

Gao Jie, Gao Bing, Liu Jianying. Research on Feedback Compensation Control for Aircraft Electric Antiskid Brake System Based on IL[J]. Journal of System Simulation, 2017, 29(7): 1625-1630.

DOI

10.16182/j.issn1004731x.joss.201707030