In recent years, with the rapid development of transportation, energy efficient optimization control technology of freight train has been widely concerned. The work of this paper is to analyze the two train operation control algorithms, fuzzy control and predictive control, and to determine which one is more suitable for the train control for the energy efficient purpose. In light of the heavy haul train dynamics model, the above two control strategies are compared with the traditional PI control in tracking performance, robustness, and energy consumption. The simulation results show that the fuzzy controller has a better speed tracking performance, robustness, and energy saving than PI controller. In contrast to PI control algorithm, the dynamic matrix predictive control algorithm has distinct advantages in terms of speed tracking, environmental unknown disturbances, and energy efficiency. The results showed that dynamic matrix predictive control is a better candidate for automatic freight train control.
[1]
T. Endo,et al.
Application of fuzzy neural network control to automatic train operation and tuning of its control rules
,
1995,
Proceedings of 1995 IEEE International Conference on Fuzzy Systems..
[2]
Katarina Kavsˇek-Biasizzo,et al.
Fuzzy predictive control of highly nonlinear pH process
,
1997
.
[3]
Hirokazu Ihara,et al.
FUZZY CONTROL FOR AUTOMATIC TRAIN OPERATION SYSTEM
,
1984
.
[4]
Eugene Khmelnitsky,et al.
On an optimal control problem of train operation
,
2000,
IEEE Trans. Autom. Control..
[5]
Chunhai Gao,et al.
A New Control Method of Automatic Train Operation in Urban Rail Transit Based on Improved Generalized Predictive Control Theory
,
2014
.