Research And Simulation On Automatic Train Operation Control Algorithm Of Multi-objective Traction In Urban Rail Transit

The urban rail transit has the advantages of high safety, convenient and fast, so it has been developing rapidly, but in recent years, with the rapid development of urban traffic, which has gradually shown its own shortcoming, especially in the aspects of transportation efficiency and rapidity. Under such a circumstance, automatic train operation(ATO) system come into being, which can replace manual driving and solve the problem of the existence of artificial driving, such as improving train speed and operational safety, reducing train delays, etc. At the same time, ATO system can also improve other performance indicators of trains operation, in order to make the train run on the different conditions of the line and improve train punctuality, comfort properties, reduce the energy consumption. Therefore, we can predict that the realization of automatic train will become the future development direction of the urban rail transit system. The main research contents of this thesis are as follows:(1) The relationship ATO, automatic train protection(ATP) and automatic train supervision(ATS), working principle, function of ATO system between and the function of speed controller are introduced, and the performances index of ATO system are described in detail. And the operating mode transition conditions, control strategy and conversion principle of ATO system are analyzed. At the same time, the train operation model has been described;(2) The basic theory and principle of fuzzy control and predictive control are introduced respectively, on this basis, combining the fuzzy control and predictive control algorithm is proposed to design a fuzzy predictive control algorithm, which is applied to the automatic train control system, and the advantages of the two algorithms are used to realize the control of the train speed. Finally, the feasibility and implementation of the fuzzy predictive control algorithm are introduced;(3) Firstly, the multi-objective model of urban rail transit train is established by using energy consumption, punctuality, parking and comfort as indicators, then the weight coefficient is solved by the entropy weight method. On the basis of a certain interval line data, for the characteristics of urban rail train running multiple objective and using genetic algorithms optimized running multi-objective model of urban rail train, and according to train traction calculation and computer simulation get the train running target curve. Finally, the PID control algorithm is applied to urban rail train system to establish PID controller in order to track the target curve. Simulation results show that the PID controller has relatively large overshoot when it follows the target curve operation, and the tracking effect of the target curve is also not ideal;(4) Fuzzy predictive controller based on fuzzy control and dynamic matrix control is designed. In the MATLAB environment for the design of the speed controller is a modeling and simulation, and the simulation results are compared with the simulation results of speed controller based on PID control algorithm. According to the results of comparison to analyze, the fuzzy predictive control is adopted to design the speed controller, which has better control effect and can meet the performance requirements of train operation, thereby the feasibility of the application of fuzzy predictive control algorithm in ATO system is verified.