High-speed Train Optimized Operation Based On Fuzzy Expert System

The optimized run of train can not be separated from the research of the problem of optimization locomotive and the manipulation environmental. How to get the best balance of these three, the secure punctual running of the train, low power and passenger ride comfort in the optimization process, which is a problem for high-speed train to meet in China. For the current situation of Chinese high-speed rail, through the study of Train Operation Performance analysis and optimized handling methods, the optimized high-speed train manipulation of fuzzy expert system is constructed to instruct train operation.First, through the study on train running performance, the constraints and the target optimized of high-speed train manipulation are determined. The principle of rational manipulation is given. Train control evaluation function is put forward. The mathematical description of train safety, punctuality manipulation, energy-saving and comfortable manipulation is obtained in accordance with the evaluation function, and manipulation method is proposed accordingly through the experience of the excellent drivers.Second, through the study on the performance of high-speed trains operation, according to the multi-objective optimization theory, multi-objective optimization model of high-speed train operation is established. Combined with clonal selection algorithm and adaptive particle swarm optimization algorithm respectively, multi-objective optimization model of high-speed train operation is optimized. The simulation experiment is done using a line in the Wuhan-Guangzhou. The results show that compared with before optimization, the high-speed trains in energy consumption, comfort and punctuality has a certain optimization effect, and two kinds of optimization results have their own advantages.Finally, according to the result of the multiple objective optimization, the manipulation of these Pareto-optimal sequence will be added in expert knowledge base. The high-speed train operation manipulation of fuzzy expert system optimization is established. Because the train control input can’t use accurate numerical to express, so it needs to describe by fuzzy amount. The reasoning machine structure of fuzzy expert system is built according to the principle of reasonable control and previous train control experience. The fuzzy reasoning mechanism and fuzzy control rule are designed. So the structure of fuzzy expert will be completed. The simulation experiment is done using a line in the Wuhan-Guangzhou. The results show that advantage combined with clonal selection algorithm and adaptive particle swarm optimization algorithm respectively can obtain better optimization effect, which can satisfy the high-speed trains in energy consumption, comfort and punctuality during the train operation.