Research On Accurate Stopping Control Of High-Speed Maglev Train

Stop-accuracy which affecting operation efficiency of High-Speed Maglev transportation system,is very crucial.Researches about accurate stopping control was abundant in the aspect of traditional wheel-rail trains,while was scarce in High-Speed Maglev trains.Maglev trains are essentially different from wheel-rail trains in terms of traction,positioning and braking,and the operation control methods are also quite different.Therefore,it would be very significant and valuable in theory and application to study the accurate stopping control of High-Speed Maglev trains.According to the regular research results about wheel-rail trains,this article proposes a brake controller for accurate stopping of High-Speed Maglev trains based on the characteristics of maglev trains.First,a dynamic model is established,according to the features of High-Speed Maglev trains.Furthermore,the P-type iterative learning controller and the optimal terminal iterative learning controller are designed respectively based on the repeatability of the train braking process,and by improving and optimizing these two algorithms,higher stop-accuracy is obtained by simulation comparison.Finally,the traction control simulation platform is built and the test verification is completed.The main contents of the thesis are as follows:1.The dynamic model of high-speed maglev train is established based on the technical characteristics(linear synchronous motors used for High-Speed Maglev trains,no wheel-rail friction during operation,electromagnetic eddy current resistance,on-board linear generator running resistance,emergency braking adopting vehicle eddy current brake and falling skid friction braking).On this basis,the dynamic model suitable for different train marshalling is obtained by quadratic fitting.2.Based on the research results of wheel-rail train parking control,an improved iterative learning control algorithm is proposed to track the target braking curve of High-Speed Maglev train.By optimizing the calculation method of the iterative operation of the system input,the impact of the initial braking position error fluctuation on the stop-accuracy is reduced.On the basis of above techniques,the 1-order and2-order P-type iterative learning controllers are designed,and the effectiveness of the improved algorithm is verified through simulation.3.Based on the assumption of constant braking force,the optimal terminal iterative learning control algorithm,which only considers the initial state and terminal state of the parking process,is applied to designing the accurate stopping controller.The theoretical proof,that the parking error is bounded when there is bounded fluctuation at the initial braking position,is given.In order to reduce the influence of the error fluctuation of the initial braking position on the stop-accuracy,the algorithm is improved,and the effectiveness of the improved algorithm is verified through simulation.4.The traction control simulation platform is built in which one High-Speed Maglev train simulation test line is set.The software function module of the precise stopping control algorithm is compiled,which is applied to the traction control simulation system,and the effectiveness of the accurate stopping controller for High-Speed Maglev train is verified.There are 79 pictures,6 tables,and 86 references.