Control strategy for optimal compromise between trip time and energy consumption in a high-speed railway

This paper presents an approach to identify a fuzzy control model for determining an economical running pattern for a high-speed railway through an optimal compromise between trip time and energy consumption. Since the linguistic model is intuitive and informative to railway operators, they can easily implement a control strategy for saving energy. The approach includes structure identification and parameter identification. It is proposed to utilize a fuzzy c-means clustering and a GA hybrid scheme to identify the structure and parameters of a fuzzy model, respectively. To evaluate the advantages and the effectiveness of the suggested approach, numerical examples are presented. Comparison shows that the proposed approach can produce a fuzzy model with higher accuracy and smaller number of rules than previously achieved in other works. To show the global optimization and local convergence of the GA hybrid-scheme, an optimization problem having a few local minima and maxima is considered.