scholarly journals Research on Multi-Objective Optimization and Control Algorithms for Automatic Train Operation

Energies ◽  
2019 ◽  
Vol 12 (20) ◽  
pp. 3842 ◽  
Author(s):  
Kai-wei Liu ◽  
Xing-Cheng Wang ◽  
Zhi-hui Qu

The automatic train operation (ATO) system of urban rail trains includes a two-layer control structure: upper-layer control and lower-layer control. The upper-layer control is to optimize the target speed curve of ATO, and the lower-layer control is the tracking by the urban rail train of the optimal target speed curve generated by the upper-layer control according to the tracking control strategy of ATO. For upper-layer control, the multi-objective model of urban rail train operation is firstly built with energy consumption, comfort, stopping accuracy, and punctuality as optimization indexes, and the entropy weight method is adopted to solve the weight coefficient of each index. Then, genetic algorithm (GA) is used to optimize the model to obtain an optimal target speed curve. In addition, an improved genetic algorithm (IGA) based on directional mutation and gene modification is proposed to improve the convergence speed and optimization effect of the algorithm. The stopping and speed constraints are added into the fitness function in the form of penalty function. For the lower-layer control, the predictive speed controller is designed according to the predictive control principle to track the target speed curve accurately. Since the inflection point area of the target speed curve is difficult to track, the softness factor in the predictive model needs to be adjusted online to improve the control accuracy of the speed. For this paper, we mainly improve the optimization and control algorithms in the upper and lower level controls of ATO. The results show that the speed controller based on predictive control algorithm has better control effect than that based on the PID control algorithm, which can meet the requirements of various performance indexes. Thus, the feasibility of predictive control algorithm in an ATO system is also verified.

2013 ◽  
Vol 433-435 ◽  
pp. 1091-1098
Author(s):  
Wei Bo Yu ◽  
Cui Yuan Feng ◽  
Ting Ting Yang ◽  
Hong Jun Li

The air precooling system heat exchange process is a complex control system with features such as: nonlinear, lag and random interference. So choose Generalized Predictive Control Algorithm that has low model dependence, good robustness and control effect, as well as easy to implement. But due to the large amount of calculation of traditional generalized predictive control and can't juggle quickness and overshoot problem, an improved generalized predictive control algorithm is proposed, then carry out the MATLAB simulation, the experimental results show that the algorithm can not only greatly reduce the amount of computation, but also can restrain the overshoot and its rapidity.


2014 ◽  
Vol 536-537 ◽  
pp. 820-823
Author(s):  
Chao Cai

Train operation regulation is the key technology to ensure the orderly operation of trains, its value has been fully realized under the background of rapid construction and high traffic density in urban rail transit. This paper did a deep analysis on different strategies and methods for urban rail transit train operation regulation and the applications of these strategies and methods in different conditions. Furthermore, an automatic train operation regulation mathematical model was established. Then developed a software system in Visual C++ and used it to analysis and test the model by data of a real metro line, the result showed that both the model and the system were available.


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