Research On The Control Strategy Of ATO Based On The Theory Of Optimal Grey Genetic Algorithm

With the rapid growth of urban population scale, the urban transportation is facing more and more high pressure. In response to this challenge, urban rail transit system must improve the efficiency of running as well as ensure the comfort of riding at the same time. Considering that train automatic driving system is a key subsystem of railway traffic control system, speed controller, core of the train automatic driving system, is of great importance. Its control algorithm quality will directly affect the safety of train operation, punctuality, comfort, energy consumption and so on, which further affects the urban rail transit’s ability to successfully deal with the increasing pressure of transportation. So many experts and scholars at home and abroad began to study on the control strategy for automatic train operation, however, most studies focused on the control strategy of the optimization of one line or one single evaluation index, and can’t do the real-time optimization in the process of train running.To cope with above problem, this paper firstly analyzes functional requirements of the ATO system, and do some study of grey theory at the same time; According to the characteristics of the ATO, this paper proves ATO is one kind of grey system, and illustrates the application of grey theory in the ATO system is feasible; After the pretreatment of train operation environment, an evaluation model for train operation was established. On the basis of improved traditional genetic algorithm and designed optimal control algorithm of the train automatic system, the algorithm will be compiled into a software of optimal control strategy. The software can generate the corresponding optimal control strategy depending on the input data, and train lines data; Secondly, this paper designed a speed controller based on grey theory, by using initial sequence generation, the grey prediction and grey decision; Finally the grey speed controller and current relatively mature fuzzy speed control are compared and matched, to do the MATLAB tracing for the speed distance curve generated by the optimal control strategy of ATO software.Applying grey theory combined with genetic theory to train automatic control system, is a new method to improve the quality of train operation control. The simulation results show that by using grey theory of speed controller, the target curve can get a better track, and the train operation evaluation indexes are more satisfying.