GROUP-SMA ALGORITHM BASED JOINT ESTIMATION OF TRAIN PARAMETER AND STATE

作者：Zheng, Wei^*; Han, Juan; Kong, Weijie; Wang, Lixiang

来源：Promet-Traffic & Transportation, 2015, 27(1): 85-95.

DOI：10.7307/ptt.v27i1.1499

• parameter estimation
• state estimation
• particle filter
• rail braking system

The braking rate and train arresting operation is important in the train braking performance. It is difficult to obtain the states of the train on time because of the measurement noise and a long calculation time. A type of Group Stochastic M-algorithm (GSMA) based on Rao-Blackwellization Particle Filter (RBPF) algorithm and Stochastic M-algorithm (SMA) is proposed in this paper. Compared with RBPF, GSMA based estimation precisions for the train braking rate and the control accelerations were improved by 78% and 62%, respectively. The calculation time of the GSMA was decreased by 70% compared with SMA.

• 出版日期2015
• 单位北京交通大学