Research On Adaptive Control Of High-speed EMU Braking Process

Due to the high speed and high safety of high-speed trains,it has become an important means of transportation for people to travel,and has played a key role in promoting the development of our national economy.However,as the speed of trains continues to increase,safety incidents such as train derailment caused by the excessive running speed occur frequently.The high-speed train braking technology is an important guarantee for the safe operation of trains.Therefore,improving the braking performance of high-speed trains has become a hot topic for experts and scholars.The difficulty of train braking technology is that it is necessary to increase the running speed of the train without affecting the comfort of passengers,and at the same time reduce the braking distance of high-speed trains as much as possible,which makes it more challenging to improve its braking performance.Therefore,it is of great significance to further study the brake control technology of high-speed trains.Considering that the demand for high-speed trains to transport passengers increases year by year,relying on the train driver to apply braking levels not only increases the driving intensity of the train driver,but also makes it difficult to ensure that high-speed trains stop on time and at fixed locations.In order to solve this problem,this paper adopts multi-level bit switching control strategy and adaptive control strategy to realize the speed tracking control of high-speed trains during the braking process.The specific research is as follows:1、In order to reflect the dynamic characteristics of the high-speed train during braking,the working principle of electric multiple unit’s braking system was analyzed.The delay and braking force increase during the generation of the train braking force were fully considered,and the mechanism model of the braking process of the high-speed train was established.The single-input single-output autoregressive model was used to describe the braking process of high-speed train,and autoregressive model’s parameters were identified using the recursive least square method.2、Using the capability of rapid learning and global approximation of the random configuration network(SCN),an SCN model was established to realize the switching of the brake stages of high-speed trains.In addition,according to the known braking characteristic curve,the current speed and braking level of the train were collected,and the corresponding train braking force was calculated,thereby realizing the speed tracking control of the train during braking.3、The use of SCN level switching and braking characteristic curves to achieve high-speed train speed tracking depends on the setting of braking characteristic curves to a certain extent.However,the train is easily affected by the external environment during the braking process,and the braking characteristics of the train may not fully meet the setting of the braking characteristic curve.In order to solve this problem,this paper adopted an indirect adaptive output feedback output tracking control algorithm to realize the adaptive tracking of the speed of the high-speed train during braking,and finally achieved the goal of asymptotic tracking of the target speed.