Abstract
The automatic train operation (ATO) system is a subsystem of an automatic train control system that is widely adopted in modern rapid transit systems. The function of ATO system is to regulate train riding comfort and smoothness during start, acceleration, constant speed travel, and fixed-point parking under the corresponding commands. This paper describes the dynamic model of a public rapid transit system and a predictive fuzzy controller with fuzzy control rules based on the operation concepts of a skilled human operator. The fuzzy rules decision-making is based on the predictive evaluation of performance indices, which includes electric power cost, riding comfort of passengers, traceability of target speed, and accuracy of stop gap. The simulation results for a planned railway trade of Taipei city rapid transit system show that the control performance of this fuzzy ATO system is better than that of the conventional PID controller. Stop gap control of fuzzy ATO can be executed successfully without the assistance of additional marker coils and vehicle alignment equipment.
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