@Article{cmc.2020.011032,
AUTHOR = {Xiaokan Wang, Qiong Wang, Shuang Liang},
TITLE = {Predictive Control Algorithm for Urban Rail Train Brake Control  System Based on T-S Fuzzy Model},
JOURNAL = {Computers, Materials \& Continua},
VOLUME = {64},
YEAR = {2020},
NUMBER = {3},
PAGES = {1859--1867},
URL = {http://www.techscience.com/cmc/v64n3/39463},
ISSN = {1546-2226},
ABSTRACT = {Urban rail transit has the advantages of large traffic capacity, high punctuality 
and zero congestion, and it plays an increasingly important role in modern urban life. 
Braking system is an important system of urban rail train, which directly affects the 
performance and safety of train operation and impacts passenger comfort. The braking 
performance of urban rail trains is directly related to the improvement of train speed and 
transportation capacity. Also, urban rail transit has the characteristics of high speed, short 
station distance, frequent starting, and frequent braking. This makes the braking control 
system constitute a time-varying, time-delaying and nonlinear control system, especially 
the braking force changes directly disturb the parking accuracy and comfort. To solve 
these issues, a predictive control algorithm based on T-S fuzzy model was proposed and 
applied to the train braking control system. Compared with the traditional PID control 
algorithm and self-adaptive fuzzy PID control algorithm, the braking capacity of urban 
rail train was improved by 8%. The algorithm can achieve fast and accurate synchronous 
braking, thereby overcoming the dynamic influence of the uncertainty, hysteresis and 
time-varying factors of the controlled object. Finally, the desired control objectives can 
be achieved, the system will have superior robustness, stability and comfort.},
DOI = {10.32604/cmc.2020.011032}
}