Maglev Automatic Train Operation (ato) System Control Algorithm And Simulation,

Maglev Automatic Train Operation (ATO) system is the keystone of maglev traffic technology. On the background of the maglev train of NUDT and the world's fair route which is being constructed in KunMing, this dissertation lays emphasis on the control algorithm, simulation of ATO, and the experiments of determination of velocity and position (DVP).Based on the analysis of the ATO's domestic and overseas research condition, the design principle of Maglev Automatic Train Control (MATC) system is brought out, and the structure of MATC as well as the performance of ATO is analyzed. Besides, PID control algorithm is introduced and the velocity closed-loop controller is designed on the basis of dynamic model for the train. Furthermore, according to KunMing world's fair route data, the ATO system with PID controller is simulated. It shows some disadvantages, and so the predictive control algorithm is brought forward to realize velocity closed-loop control. It uses online roll optimizing index and feedback tuning strategy, conquers the dynamic effects such as uncertainty of controlled-object, delay and time-varying, and achieves the predictive control target---reference track input and better stability and robust performance. Furthermore, it obtains a relatively satisfactory simulation result by using the predictive controller.After analyzing the structure of ATO system, the hardware platform scheme using ARM microprocessor is designed. Some expanding experiments on according interface are done with ARM exploitation board which is used as experimental platform. Besides, compiling, loading, and debugging of the ARM programs are briefly introduced. Determination of velocity and position is the technical foundation of realizing ATO. TheDVP method which adapts to diverse sleeper width is brought out, and it runs well on the maglev train.