Title :
A realization and simulation of ATO speed control module—Predictive fuzzy control algorithm
Author :
Xiaofan Mo ; Tao Tang ; Chunzhao Dong ; Yuan Yao ; Xiaofei Yao
Author_Institution :
Railway Safety Technol. Res. Centre, Beijing Jiaotong Univ., Beijing, China
fDate :
Aug. 30 2013-Sept. 1 2013
Abstract :
Considering the multi-functional needs of the Automatic Train Operation System (ATO), this paper uses a method combined the prediction algorithm and the multi-variable fuzzy control algorithm to design the ATO automatic speed control module. It divides the operation process into three conditions, includes starting, cruising and parking, and assigns different weights to the three condition depend on the performance of comfort, energy saving and stopping accuracy, and uses fuzzy control algorithm on the two variables of displacement and velocity, at last gets the comprehensive control value. Then the control system sends the control values which would be used in the next cycle to calculate the actual curve module, so that the system can achieve automatic operation. In this paper, the writer simulated the system, and verified the speed control function of the ATO speed control module, through the analysis of test results that the system has reached the desired control effect.
Keywords :
control system synthesis; displacement control; ergonomics; fuzzy control; multivariable control systems; predictive control; rail traffic control; velocity control; ATO speed control module realization; ATO speed control module simulation; automatic ATO speed control module design; automatic train operation system; comfort performance; comprehensive control value; cruising condition; curve module; displacement variables; energy saving; operation process; parking condition; predictive multivariable fuzzy control algorithm; starting condition; stopping accuracy; velocity variables; weight assignment; Acceleration; Accuracy; Algorithm design and analysis; Fuzzy control; Prediction algorithms; Velocity control; automatic speed control; fuzzy control; multi-variables; prediction control;
Conference_Titel :
Intelligent Rail Transportation (ICIRT), 2013 IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4673-5278-9
DOI :
10.1109/ICIRT.2013.6696305