Speed Tracking Based Energy-Efficient Freight Train Control Through Multi-Algorithms Combination

Based on the characteristics of freight train control, which are nonlinear, time-delay, with multi-constraint and multiobjective, this paper focuses on speed tracking problem. Firstly, in a gradual process, a multi-modal fuzzy PID (MM-FPID) control algorithm is presented on the basis of a brief analysis of PI and PID control, which is generally used to train control in active services. Secondly, in order to deal with the time-delay problem of freight train, the paper adopts an approach of traction force feed-forward, which greatly improves the dynamic performance of the controller. Thirdly, for the overspeed brake problem caused by speed overshoot, the strategy of adaptive traction force limitation is adopted, and we get satisfactory results without increasing the safety speed margin. Fourthly, inspired by the selflearning characteristic of neural networks (NNs), an integrated controller of MM-FPID and NNs is proposed. Finally, with the help of a computer simulation platform, the paper puts forward a set of simulations, comparing the MM-FPID and the integrated control method with classical PID and fuzzy control. The results show that both MM-FPID and the integrated controller has satisfactory control effect, and their multi-modal structure makes it easy to fit different applications well, while the integrated controller has more potential in self-learning.